<a href="https://github.com/dd-consulting">
     <img src="../reference/GZ_logo.png" width="60" align="right">
</a>
<h1>
    One-Stop Analytics: Predictive Modeling (Rattle)
</h1>

Case Study of Autism Spectrum Disorder (ASD) with R


[ United States ]

Centers for Disease Control and Prevention (CDC) - Autism Spectrum Disorder (ASD)

Autism spectrum disorder (ASD) is a developmental disability that can cause significant social, communication and behavioral challenges. CDC is committed to continuing to provide essential data on ASD, search for factors that put children at risk for ASD and possible causes, and develop resources that help identify children with ASD as early as possible.

https://www.cdc.gov/ncbddd/autism/data/index.html

[ Singapore ]

TODAY Online - More preschoolers diagnosed with developmental issues

Doctors cited better awareness among parents and preschool teachers, leading to early referrals for diagnosis.

https://www.gov.sg/news/content/today-online-more-preschoolers-diagnosed-with-developmental-issues

https://www.pathlight.org.sg/

<a href="">
     <img src="" width="60" align="right">
</a>

Workshop Objective:

Use R to predict Autism Spectrum Disorder (ASD) prevalence.

https://www.cdc.gov/ncbddd/autism/data/index.html

  • Rattle

  • Rattle: Import Data

  • Rattle: EDA Explore & Test

  • Rattle: Process & Transform Data

    Predict Prevelance Risk Levels (Classification)

  • Rattle: Train Model (Classification)

    • Multi-Class Model: Decision Tree (DT)

    • Multi-Class Model: Random Forest (RF)

    • Multi-Class Model: Support Vector Machines (SVM)

    • Multi-Class Model: Multinomial Logistic Regression (MLR)

    • Binary-Class Model: Boost (AdaBoost & XgBoost)

    • Binary-Class Model: Neural Net (NN)

  • Rattle: Evaluate Model (Classification)

    Predict Prevelance (Regression)

  • Rattle: Train Model (Regression)

    • Regression Model: Decision Tree (DT)

    • Regression Model: Random Forest (RF)

    • Regression Model: Linear Regression (LR)

    • Regressions Model: Neural Net (NN)

  • Rattle: Evaluate Model (Regression)

  • Rattle: Improve Model

  • Rattle: Save Model & Log

  • Workshop Submission

  • Appendices

<a href="">
     <img src="" width="750" align="center">
</a>
library("repr") # Show graphs in-line notebook

Obtain current R working directory

getwd()
## [1] "/media/sf_vm_shared_folder/git/DDC-ASD/model_R"

Set new R working directory

# setwd("/media/sf_vm_shared_folder/git/DDC/DDC-ASD/model_R")
# setwd('~/Desktop/admin-desktop/vm_shared_folder/git/DDC-ASD/model_R')
getwd()
## [1] "/media/sf_vm_shared_folder/git/DDC-ASD/model_R"
# Adjust in-line plot size to M x N
options(repr.plot.width=8, repr.plot.height=5)
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle

Rattle — the R Analytical Tool To Learn Easily — is a popular open-source GUI for data mining using R.

https://rattle.togaware.com/

https://journal.r-project.org/archive/2009-2/RJournal_2009-2_Williams.pdf

<h3>
Rattle
</h3>
if(!require(rattle)){install.packages("rattle")}
## Loading required package: rattle
## Rattle: A free graphical interface for data science with R.
## Version 5.2.0 Copyright (c) 2006-2018 Togaware Pty Ltd.
## Type 'rattle()' to shake, rattle, and roll your data.
library('rattle')

#=======================================================================

# Rattle is Copyright (c) 2006-2018 Togaware Pty Ltd.
# It is free (as in libre) open source software.
# It is licensed under the GNU General Public License,
# Version 2. Rattle comes with ABSOLUTELY NO WARRANTY.
# Rattle was written by Graham Williams with contributions
# from others as acknowledged in 'library(help=rattle)'.
# Visit https://rattle.togaware.com/ for details.

#=======================================================================
# Rattle timestamp: 2019-12-23 09:42:23 x86_64-pc-linux-gnu 

# Rattle version 5.3.0 user 'iss-user'

# This log captures interactions with Rattle as an R script. 

# For repeatability, export this activity log to a 
# file, like 'model.R' using the Export button or 
# through the Tools menu. Th script can then serve as a 
# starting point for developing your own scripts. 
# After xporting to a file called 'model.R', for exmample, 
# you can type into a new R Console the command 
# "source('model.R')" and so repeat all actions. Generally, 
# you will want to edit the file to suit your own needs. 
# You can also edit this log in place to record additional 
# information before exporting the script. 
 
# Note that saving/loading projects retains this log.

# We begin most scripts by loading the required packages.
# Here are some initial packages to load and others will be
# identified as we proceed through the script. When writing
# our own scripts we often collect together the library
# commands at the beginning of the script here.

library(rattle)   # Access the weather dataset and utilities.
library(magrittr) # Utilise %>% and %<>% pipeline operators.

# This log generally records the process of building a model. 
# However, with very little effort the log can also be used 
# to score a new dataset. The logical variable 'building' 
# is used to toggle between generating transformations, 
# when building a model and using the transformations, 
# when scoring a dataset.

building <- TRUE
scoring  <- ! building

# A pre-defined value is used to reset the random seed 
# so that results are repeatable.

crv$seed <- 88
set.seed(88)
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Import Data

<h3>
Rattle: Import Data
</h3>

Use Case Data: “../dataset/ADV_ASD_State_R.csv”

#=======================================================================
# Rattle timestamp: 2019-12-23 10:01:39 x86_64-pc-linux-gnu 

# Load a dataset from file.

fname <- "../dataset/ADV_ASD_State_R.csv" 
crs$dataset <- read.csv(fname, na.strings=c(".", "NA", "", "?"), strip.white=TRUE, encoding="UTF-8")

#=======================================================================
# Rattle timestamp: 2019-12-23 10:01:40 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(crv$seed)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("State", "Denominator", "Prevalence",
                   "Lower.CI", "Upper.CI", "Year", "Source_Full1",
                   "State_Full1", "State_Full2", "Numerator_ASD",
                   "Numerator_NonASD", "Proportion",
                   "Chi_Wilson_Corrected_Lower.CI",
                   "Chi_Wilson_Corrected_Upper.CI",
                   "Male.Prevalence", "Male.Lower.CI",
                   "Male.Upper.CI", "Female.Prevalence",
                   "Female.Lower.CI", "Female.Upper.CI",
                   "Non.hispanic.white.Prevalence",
                   "Non.hispanic.white.Lower.CI",
                   "Non.hispanic.white.Upper.CI",
                   "Non.hispanic.black.Prevalence",
                   "Non.hispanic.black.Lower.CI",
                   "Non.hispanic.black.Upper.CI",
                   "Hispanic.Prevalence", "Hispanic.Lower.CI",
                   "Hispanic.Upper.CI",
                   "Asian.or.Pacific.Islander.Prevalence",
                   "Asian.or.Pacific.Islander.Lower.CI",
                   "Asian.or.Pacific.Islander.Upper.CI", "Source_UC",
                   "Source_Full3", "Prevalence_Risk2",
                   "Prevalence_Risk4", "Year_Factor")

crs$numeric   <- c("Denominator", "Prevalence", "Lower.CI",
                   "Upper.CI", "Year", "Numerator_ASD",
                   "Numerator_NonASD", "Proportion",
                   "Chi_Wilson_Corrected_Lower.CI",
                   "Chi_Wilson_Corrected_Upper.CI",
                   "Male.Prevalence", "Male.Lower.CI",
                   "Male.Upper.CI", "Female.Prevalence",
                   "Female.Lower.CI", "Female.Upper.CI",
                   "Non.hispanic.white.Prevalence",
                   "Non.hispanic.white.Lower.CI",
                   "Non.hispanic.white.Upper.CI",
                   "Non.hispanic.black.Prevalence",
                   "Non.hispanic.black.Lower.CI",
                   "Non.hispanic.black.Upper.CI",
                   "Hispanic.Prevalence", "Hispanic.Lower.CI",
                   "Hispanic.Upper.CI",
                   "Asian.or.Pacific.Islander.Prevalence",
                   "Asian.or.Pacific.Islander.Lower.CI",
                   "Asian.or.Pacific.Islander.Upper.CI",
                   "Year_Factor")

crs$categoric <- c("State", "Source_Full1", "State_Full1",
                   "State_Full2", "Source_UC", "Source_Full3",
                   "Prevalence_Risk2", "Prevalence_Risk4")

crs$target    <- "Source"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- NULL
crs$weights   <- NULL

#=======================================================================
# Rattle timestamp: 2019-12-23 10:05:28 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(88)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("State", "Denominator", "Prevalence",
                   "Lower.CI", "Upper.CI", "Year", "Source",
                   "Source_Full1", "State_Full1", "State_Full2",
                   "Numerator_ASD", "Numerator_NonASD", "Proportion",
                   "Chi_Wilson_Corrected_Lower.CI",
                   "Chi_Wilson_Corrected_Upper.CI",
                   "Male.Prevalence", "Male.Lower.CI",
                   "Male.Upper.CI", "Female.Prevalence",
                   "Female.Lower.CI", "Female.Upper.CI",
                   "Non.hispanic.white.Prevalence",
                   "Non.hispanic.white.Lower.CI",
                   "Non.hispanic.white.Upper.CI",
                   "Non.hispanic.black.Prevalence",
                   "Non.hispanic.black.Lower.CI",
                   "Non.hispanic.black.Upper.CI",
                   "Hispanic.Prevalence", "Hispanic.Lower.CI",
                   "Hispanic.Upper.CI",
                   "Asian.or.Pacific.Islander.Prevalence",
                   "Asian.or.Pacific.Islander.Lower.CI",
                   "Asian.or.Pacific.Islander.Upper.CI", "Source_UC",
                   "Source_Full3", "Prevalence_Risk2", "Year_Factor")

crs$numeric   <- c("Denominator", "Prevalence", "Lower.CI",
                   "Upper.CI", "Year", "Numerator_ASD",
                   "Numerator_NonASD", "Proportion",
                   "Chi_Wilson_Corrected_Lower.CI",
                   "Chi_Wilson_Corrected_Upper.CI",
                   "Male.Prevalence", "Male.Lower.CI",
                   "Male.Upper.CI", "Female.Prevalence",
                   "Female.Lower.CI", "Female.Upper.CI",
                   "Non.hispanic.white.Prevalence",
                   "Non.hispanic.white.Lower.CI",
                   "Non.hispanic.white.Upper.CI",
                   "Non.hispanic.black.Prevalence",
                   "Non.hispanic.black.Lower.CI",
                   "Non.hispanic.black.Upper.CI",
                   "Hispanic.Prevalence", "Hispanic.Lower.CI",
                   "Hispanic.Upper.CI",
                   "Asian.or.Pacific.Islander.Prevalence",
                   "Asian.or.Pacific.Islander.Lower.CI",
                   "Asian.or.Pacific.Islander.Upper.CI",
                   "Year_Factor")

crs$categoric <- c("State", "Source", "Source_Full1",
                   "State_Full1", "State_Full2", "Source_UC",
                   "Source_Full3", "Prevalence_Risk2")

crs$target    <- "Prevalence_Risk4"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- NULL
crs$weights   <- NULL
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: EDA Explore & Test

if(!require(Hmisc)){install.packages("Hmisc")}
## Loading required package: Hmisc
## Loading required package: lattice
## Loading required package: survival
## Loading required package: Formula
## Loading required package: ggplot2
## 
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:base':
## 
##     format.pval, units
library('Hmisc')
if(!require(fBasics)){install.packages("fBasics")}
## Loading required package: fBasics
## Loading required package: timeDate
## Loading required package: timeSeries
library('fBasics')
if(!require(mice)){install.packages("mice")}
## Loading required package: mice
## 
## Attaching package: 'mice'
## The following objects are masked from 'package:base':
## 
##     cbind, rbind
library('mice')
if(!require(descr)){install.packages("descr")}
## Loading required package: descr
library('descr')
<h3>
Rattle: EDA Explore & Test: Summary
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 10:12:32 x86_64-pc-linux-gnu 

# The 'Hmisc' package provides the 'contents' function.

library(Hmisc, quietly=TRUE)

# Obtain a summary of the dataset.

contents(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)])
## 
## Data frame:crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)]    1184 observations and 38 variables    Maximum # NAs:1133
## 
## 
##                                      Levels Storage  NAs
## State                                    51 integer    0
## Denominator                                 integer    0
## Prevalence                                   double    0
## Lower.CI                                     double    0
## Upper.CI                                     double    0
## Year                                        integer    0
## Source                                    4 integer    0
## Source_Full1                              4 integer    0
## State_Full1                              51 integer    0
## State_Full2                              51 integer    0
## Numerator_ASD                               integer    0
## Numerator_NonASD                            integer    0
## Proportion                                   double    0
## Chi_Wilson_Corrected_Lower.CI                double    0
## Chi_Wilson_Corrected_Upper.CI                double    0
## Male.Prevalence                              double 1125
## Male.Lower.CI                                double 1125
## Male.Upper.CI                                double 1125
## Female.Prevalence                            double 1125
## Female.Lower.CI                              double 1125
## Female.Upper.CI                              double 1125
## Non.hispanic.white.Prevalence                double 1125
## Non.hispanic.white.Lower.CI                  double 1125
## Non.hispanic.white.Upper.CI                  double 1125
## Non.hispanic.black.Prevalence                double 1125
## Non.hispanic.black.Lower.CI                  double 1125
## Non.hispanic.black.Upper.CI                  double 1125
## Hispanic.Prevalence                          double 1129
## Hispanic.Lower.CI                            double 1129
## Hispanic.Upper.CI                            double 1129
## Asian.or.Pacific.Islander.Prevalence         double 1133
## Asian.or.Pacific.Islander.Lower.CI           double 1133
## Asian.or.Pacific.Islander.Upper.CI           double 1133
## Source_UC                                 4 integer    0
## Source_Full3                              4 integer    0
## Prevalence_Risk2                          2 integer    0
## Year_Factor                                 integer    0
## Prevalence_Risk4                          4 integer    0
## 
## +----------------+------------------------------------------------------------+
## |Variable        |Levels                                                      |
## +----------------+------------------------------------------------------------+
## |State           |AK,AL,AR,AZ,CA,CO,CT,DC,DE,FL,GA,HI,IA,ID,IL,IN,KS,KY,LA,MA |
## |                |MD,ME,MI,MN,MO,MS,MT,NC,ND,NE,NH,NJ,NM,NV,NY,OH,OK,OR,PA,RI |
## |                |SC,SD,TN,TX,UT,VA,VT,WA,WI,WV,WY                            |
## +----------------+------------------------------------------------------------+
## |Source          |addm,medi,nsch,sped                                         |
## +----------------+------------------------------------------------------------+
## |Source_Full1    |Autism & Developmental Disabilities Monitoring Network      |
## |                |Medicaid,National Survey of Children's Health               |
## |                |Special Education Child Count                               |
## +----------------+------------------------------------------------------------+
## |State_Full1     |Alabama,Alaska,Arizona,Arkansas,California,Colorado         |
## |                |Connecticut,Delaware,District of Columbia,Florida,Georgia   |
## |                |Hawaii,Idaho,Illinois,Indiana,Iowa,Kansas,Kentucky,Louisiana|
## |                |Maine,Maryland,Massachusetts,Michigan,Minnesota,Mississippi |
## |                |Missouri,Montana,Nebraska,Nevada,New Hampshire,New Jersey   |
## |                |New Mexico,New York,North Carolina,North Dakota,Ohio        |
## |                |Oklahoma,Oregon,Pennsylvania,Rhode Island,South Carolina    |
## |                |South Dakota,Tennessee,Texas,Utah,Vermont,Virginia          |
## |                |Washington,West Virginia,Wisconsin,Wyoming                  |
## +----------------+------------------------------------------------------------+
## |State_Full2     |AK-Alaska,AL-Alabama,AR-Arkansas,AZ-Arizona,CA-California   |
## |                |CO-Colorado,CT-Connecticut,DC-District of Columbia          |
## |                |DE-Delaware,FL-Florida,GA-Georgia,HI-Hawaii,IA-Iowa,ID-Idaho|
## |                |IL-Illinois,IN-Indiana,KS-Kansas,KY-Kentucky,LA-Louisiana   |
## |                |MA-Massachusetts,MD-Maryland,ME-Maine,MI-Michigan           |
## |                |MN-Minnesota,MO-Missouri,MS-Mississippi,MT-Montana          |
## |                |NC-North Carolina,ND-North Dakota,NE-Nebraska               |
## |                |NH-New Hampshire,NJ-New Jersey,NM-New Mexico,NV-Nevada      |
## |                |NY-New York,OH-Ohio,OK-Oklahoma,OR-Oregon,PA-Pennsylvania   |
## |                |RI-Rhode Island,SC-South Carolina,SD-South Dakota           |
## |                |TN-Tennessee,TX-Texas,UT-Utah,VA-Virginia,VT-Vermont        |
## |                |WA-Washington,WI-Wisconsin,WV-West Virginia,WY-Wyoming      |
## +----------------+------------------------------------------------------------+
## |Source_UC       |ADDM,MEDI,NSCH,SPED                                         |
## +----------------+------------------------------------------------------------+
## |Source_Full3    |ADDM Autism & Developmental Disabilities Monitoring Network |
## |                |MEDI Medicaid,NSCH National Survey of Children's Health     |
## |                |SPED Special Education Child Count                          |
## +----------------+------------------------------------------------------------+
## |Prevalence_Risk2|High,Low                                                    |
## +----------------+------------------------------------------------------------+
## |Prevalence_Risk4|High,Low,Medium,Very High                                   |
## +----------------+------------------------------------------------------------+
summary(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)])
##      State       Denominator        Prevalence        Lower.CI     
##  GA     :  31   Min.   :   1016   Min.   : 0.500   Min.   : 0.400  
##  PA     :  30   1st Qu.: 108856   1st Qu.: 3.100   1st Qu.: 3.000  
##  MO     :  29   Median : 371602   Median : 5.700   Median : 5.400  
##  AR     :  27   Mean   : 616915   Mean   : 7.213   Mean   : 6.457  
##  NC     :  27   3rd Qu.: 782692   3rd Qu.: 9.200   3rd Qu.: 8.600  
##  SC     :  27   Max.   :5824922   Max.   :37.900   Max.   :24.900  
##  (Other):1013                                                      
##     Upper.CI           Year       Source   
##  Min.   : 0.600   Min.   :2000   addm: 59  
##  1st Qu.: 3.400   1st Qu.:2004   medi:461  
##  Median : 6.000   Median :2008   nsch: 68  
##  Mean   : 8.261   Mean   :2008   sped:596  
##  3rd Qu.: 9.725   3rd Qu.:2011             
##  Max.   :58.600   Max.   :2016             
##                                            
##                                                  Source_Full1
##  Autism & Developmental Disabilities Monitoring Network: 59  
##  Medicaid                                              :461  
##  National Survey of Children's Health                  : 68  
##  Special Education Child Count                         :596  
##                                                              
##                                                              
##                                                              
##          State_Full1              State_Full2   Numerator_ASD  
##  Georgia       :  31   GA-Georgia       :  31   Min.   :   11  
##  Pennsylvania  :  30   PA-Pennsylvania  :  30   1st Qu.:  509  
##  Missouri      :  29   MO-Missouri      :  29   Median : 1493  
##  Arkansas      :  27   AR-Arkansas      :  27   Mean   : 3754  
##  North Carolina:  27   NC-North Carolina:  27   3rd Qu.: 4211  
##  South Carolina:  27   SC-South Carolina:  27   Max.   :73394  
##  (Other)       :1013   (Other)          :1013                  
##  Numerator_NonASD    Proportion        Chi_Wilson_Corrected_Lower.CI
##  Min.   :    985   Min.   :0.0004932   Min.   : 0.3365              
##  1st Qu.: 108492   1st Qu.:0.0031032   1st Qu.: 2.9370              
##  Median : 370282   Median :0.0056999   Median : 5.3765              
##  Mean   : 613161   Mean   :0.0072107   Mean   : 6.5342              
##  3rd Qu.: 776333   3rd Qu.:0.0092017   3rd Qu.: 8.6034              
##  Max.   :5795215   Max.   :0.0375767   Max.   :28.2071              
##                                                                     
##  Chi_Wilson_Corrected_Upper.CI Male.Prevalence Male.Lower.CI   Male.Upper.CI  
##  Min.   : 0.6106               Min.   : 6.80   Min.   : 5.00   Min.   : 9.30  
##  1st Qu.: 3.4171               1st Qu.:12.20   1st Qu.:10.60   1st Qu.:14.65  
##  Median : 6.0332               Median :18.30   Median :16.10   Median :20.80  
##  Mean   : 8.0668               Mean   :18.42   Mean   :16.23   Mean   :20.93  
##  3rd Qu.: 9.7262               3rd Qu.:23.10   3rd Qu.:20.80   3rd Qu.:25.60  
##  Max.   :49.7627               Max.   :39.10   Max.   :36.20   Max.   :44.90  
##                                NA's   :1125    NA's   :1125    NA's   :1125   
##  Female.Prevalence Female.Lower.CI Female.Upper.CI 
##  Min.   :1.500     Min.   :0.900   Min.   : 2.400  
##  1st Qu.:2.900     1st Qu.:2.050   1st Qu.: 3.900  
##  Median :3.800     Median :2.900   Median : 5.300  
##  Mean   :4.236     Mean   :3.249   Mean   : 5.556  
##  3rd Qu.:5.500     3rd Qu.:4.450   3rd Qu.: 6.800  
##  Max.   :9.300     Max.   :7.900   Max.   :11.600  
##  NA's   :1125      NA's   :1125    NA's   :1125    
##  Non.hispanic.white.Prevalence Non.hispanic.white.Lower.CI
##  Min.   : 3.80                 Min.   : 2.60              
##  1st Qu.: 7.95                 1st Qu.: 6.80              
##  Median :12.00                 Median :10.50              
##  Mean   :12.31                 Mean   :10.59              
##  3rd Qu.:15.65                 3rd Qu.:13.85              
##  Max.   :26.60                 Max.   :24.00              
##  NA's   :1125                  NA's   :1125               
##  Non.hispanic.white.Upper.CI Non.hispanic.black.Prevalence
##  Min.   : 5.60               Min.   : 3.00                
##  1st Qu.: 9.55               1st Qu.: 5.90                
##  Median :13.80               Median : 9.20                
##  Mean   :14.35               Mean   :10.04                
##  3rd Qu.:18.40               3rd Qu.:12.50                
##  Max.   :29.80               Max.   :27.20                
##  NA's   :1125                NA's   :1125                 
##  Non.hispanic.black.Lower.CI Non.hispanic.black.Upper.CI Hispanic.Prevalence
##  Min.   : 0.900              Min.   : 4.70               Min.   : 0.300     
##  1st Qu.: 4.200              1st Qu.: 8.35               1st Qu.: 4.550     
##  Median : 6.400              Median :12.90               Median : 7.000     
##  Mean   : 7.498              Mean   :13.95               Mean   : 7.518     
##  3rd Qu.: 9.500              3rd Qu.:18.35               3rd Qu.:10.050     
##  Max.   :21.700              Max.   :34.20               Max.   :20.900     
##  NA's   :1125                NA's   :1125                NA's   :1129       
##  Hispanic.Lower.CI Hispanic.Upper.CI Asian.or.Pacific.Islander.Prevalence
##  Min.   : 0.000    Min.   : 2.10     Min.   : 1.000                      
##  1st Qu.: 2.350    1st Qu.: 9.65     1st Qu.: 4.050                      
##  Median : 4.500    Median :11.30     Median : 7.900                      
##  Mean   : 5.153    Mean   :12.10     Mean   : 8.796                      
##  3rd Qu.: 7.350    3rd Qu.:13.55     3rd Qu.:12.100                      
##  Max.   :15.100    Max.   :29.70     Max.   :21.900                      
##  NA's   :1129      NA's   :1129      NA's   :1133                        
##  Asian.or.Pacific.Islander.Lower.CI Asian.or.Pacific.Islander.Upper.CI
##  Min.   : 0.20                      Min.   : 7.40                     
##  1st Qu.: 1.40                      1st Qu.:12.75                     
##  Median : 4.60                      Median :18.30                     
##  Mean   : 4.92                      Mean   :18.36                     
##  3rd Qu.: 7.35                      3rd Qu.:22.85                     
##  Max.   :16.00                      Max.   :32.00                     
##  NA's   :1133                       NA's   :1133                      
##  Source_UC                                                       Source_Full3
##  ADDM: 59   ADDM Autism & Developmental Disabilities Monitoring Network: 59  
##  MEDI:461   MEDI Medicaid                                              :461  
##  NSCH: 68   NSCH National Survey of Children's Health                  : 68  
##  SPED:596   SPED Special Education Child Count                         :596  
##                                                                              
##                                                                              
##                                                                              
##  Prevalence_Risk2  Year_Factor    Prevalence_Risk4
##  High:675         Min.   :2000   High     :208    
##  Low :509         1st Qu.:2004   Low      :509    
##                   Median :2008   Medium   :418    
##                   Mean   :2008   Very High: 49    
##                   3rd Qu.:2011                    
##                   Max.   :2016                    
## 
# The 'Hmisc' package provides the 'describe' function.

library(Hmisc, quietly=TRUE)

# Generate a description of the dataset.

describe(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)])
## crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)] 
## 
##  38  Variables      1184  Observations
## --------------------------------------------------------------------------------
## State 
##        n  missing distinct 
##     1184        0       51 
## 
## lowest : AK AL AR AZ CA, highest: VT WA WI WV WY
## --------------------------------------------------------------------------------
## Denominator 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1177        1   616915   729380     1655    33401 
##      .25      .50      .75      .90      .95 
##   108856   371602   782692  1471583  1888283 
## 
## lowest :    1016    1051    1075    1084    1089
## highest: 5783968 5784387 5801532 5812940 5824922
## --------------------------------------------------------------------------------
## Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0      215        1    7.213    5.751     1.50     1.90 
##      .25      .50      .75      .90      .95 
##     3.10     5.70     9.20    14.20    19.07 
## 
## lowest :  0.5  0.6  0.7  0.8  0.9, highest: 32.5 35.1 35.3 37.0 37.9
## --------------------------------------------------------------------------------
## Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0      187        1    6.457    4.834     1.40     1.80 
##      .25      .50      .75      .90      .95 
##     3.00     5.40     8.60    12.80    15.88 
## 
## lowest :  0.4  0.5  0.6  0.7  0.8, highest: 22.6 23.0 24.2 24.3 24.9
## --------------------------------------------------------------------------------
## Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0      235        1    8.261     7.24    1.600    2.100 
##      .25      .50      .75      .90      .95 
##    3.400    6.000    9.725   15.570   21.685 
## 
## lowest :  0.6  0.7  0.8  0.9  1.0, highest: 53.4 54.8 55.3 56.1 58.6
## --------------------------------------------------------------------------------
## Year 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0       17    0.996     2008    5.339     2000     2001 
##      .25      .50      .75      .90      .95 
##     2004     2008     2011     2014     2016 
## 
## lowest : 2000 2001 2002 2003 2004, highest: 2012 2013 2014 2015 2016
##                                                                             
## Value       2000  2001  2002  2003  2004  2005  2006  2007  2008  2009  2010
## Frequency     74    67    76    66    73    71    79    74    91    71    78
## Proportion 0.062 0.057 0.064 0.056 0.062 0.060 0.067 0.062 0.077 0.060 0.066
##                                               
## Value       2011  2012  2013  2014  2015  2016
## Frequency     75   114    32    43    37    63
## Proportion 0.063 0.096 0.027 0.036 0.031 0.053
## --------------------------------------------------------------------------------
## Source 
##        n  missing distinct 
##     1184        0        4 
##                                   
## Value       addm  medi  nsch  sped
## Frequency     59   461    68   596
## Proportion 0.050 0.389 0.057 0.503
## --------------------------------------------------------------------------------
## Source_Full1 
##        n  missing distinct 
##     1184        0        4 
## 
## Autism & Developmental Disabilities Monitoring Network (59, 0.050), Medicaid
## (461, 0.389), National Survey of Children's Health (68, 0.057), Special
## Education Child Count (596, 0.503)
## --------------------------------------------------------------------------------
## State_Full1 
##        n  missing distinct 
##     1184        0       51 
## 
## lowest : Alabama       Alaska        Arizona       Arkansas      California   
## highest: Virginia      Washington    West Virginia Wisconsin     Wyoming      
## --------------------------------------------------------------------------------
## State_Full2 
##        n  missing distinct 
##     1184        0       51 
## 
## lowest : AK-Alaska        AL-Alabama       AR-Arkansas      AZ-Arizona       CA-California   
## highest: VT-Vermont       WA-Washington    WI-Wisconsin     WV-West Virginia WY-Wyoming      
## --------------------------------------------------------------------------------
## Numerator_ASD 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1022        1     3754     4962    41.15   184.20 
##      .25      .50      .75      .90      .95 
##   509.00  1493.00  4211.00  9655.90 14644.40 
## 
## lowest :    11    12    14    15    16, highest: 54338 59008 63530 68610 73394
## --------------------------------------------------------------------------------
## Numerator_NonASD 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1181        1   613161   724881     1625    33153 
##      .25      .50      .75      .90      .95 
##   108492   370282   776333  1460859  1878925 
## 
## lowest :     985    1022    1041    1055    1058
## highest: 5744637 5766455 5776005 5791432 5795215
## --------------------------------------------------------------------------------
## Proportion 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1184        1 0.007211 0.005746 0.001500 0.001901 
##      .25      .50      .75      .90      .95 
## 0.003103 0.005700 0.009202 0.014194 0.018892 
## 
## lowest : 0.000493206 0.000499319 0.000500844 0.000502858 0.000597211
## highest: 0.032258065 0.034799737 0.035610465 0.036912752 0.037576687
## --------------------------------------------------------------------------------
## Chi_Wilson_Corrected_Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1184        1    6.534     4.98    1.377    1.764 
##      .25      .50      .75      .90      .95 
##    2.937    5.376    8.603   12.981   16.034 
## 
## lowest :  0.3364642  0.4024432  0.4073929  0.4079149  0.4893931
## highest: 23.8020776 26.4171431 26.7255225 27.2505970 28.2070707
## --------------------------------------------------------------------------------
## Chi_Wilson_Corrected_Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0     1184        1    8.067     6.86    1.622    2.068 
##      .25      .50      .75      .90      .95 
##    3.417    6.033    9.726   15.582   21.687 
## 
## lowest :  0.6105725  0.6150527  0.6274647  0.7182531  0.7280576
## highest: 44.4072525 45.6058947 47.1761133 49.6653983 49.7627137
## --------------------------------------------------------------------------------
## Male.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       52        1    18.42    8.526     8.78     9.18 
##      .25      .50      .75      .90      .95 
##    12.20    18.30    23.10    27.14    32.85 
## 
## lowest :  6.8  7.9  8.6  8.8  8.9, highest: 28.0 32.7 34.2 39.0 39.1
## --------------------------------------------------------------------------------
## Male.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       53        1    16.23    7.927     7.28     7.76 
##      .25      .50      .75      .90      .95 
##    10.60    16.10    20.80    24.50    28.16 
## 
## lowest :  5.0  6.7  7.1  7.3  7.4, highest: 25.5 28.1 28.7 33.8 36.2
## --------------------------------------------------------------------------------
## Male.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       49        1    20.93    9.185    10.60    11.04 
##      .25      .50      .75      .90      .95 
##    14.65    20.80    25.60    30.06    38.45 
## 
## lowest :  9.3 10.6 10.8 11.1 11.4, highest: 30.8 38.2 40.7 42.2 44.9
## --------------------------------------------------------------------------------
## Female.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       39    0.999    4.236     1.91     2.18     2.30 
##      .25      .50      .75      .90      .95 
##     2.90     3.80     5.50     6.40     6.66 
## 
## lowest : 1.5 2.0 2.2 2.3 2.4, highest: 6.5 6.6 7.2 8.5 9.3
## --------------------------------------------------------------------------------
## Female.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       38    0.999    3.249    1.662     1.48     1.60 
##      .25      .50      .75      .90      .95 
##     2.05     2.90     4.45     5.12     5.30 
## 
## lowest : 0.9 1.3 1.5 1.6 1.7, highest: 5.1 5.2 5.3 6.3 7.9
## --------------------------------------------------------------------------------
## Female.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       41    0.999    5.556    2.264     2.88     3.10 
##      .25      .50      .75      .90      .95 
##     3.90     5.30     6.80     7.92     9.19 
## 
## lowest :  2.4  2.7  2.9  3.1  3.4, highest:  8.2  9.1 10.0 10.9 11.6
## --------------------------------------------------------------------------------
## Non.hispanic.white.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       52        1    12.31    5.895     5.44     5.98 
##      .25      .50      .75      .90      .95 
##     7.95    12.00    15.65    18.64    20.73 
## 
## lowest :  3.8  4.6  4.9  5.5  5.8, highest: 19.5 20.7 21.0 24.3 26.6
## --------------------------------------------------------------------------------
## Non.hispanic.white.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       49        1    10.59     5.35     4.25     4.96 
##      .25      .50      .75      .90      .95 
##     6.80    10.50    13.85    16.34    16.97 
## 
## lowest :  2.6  3.2  3.8  4.3  4.6, highest: 16.5 16.8 18.5 19.8 24.0
## --------------------------------------------------------------------------------
## Non.hispanic.white.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       51        1    14.35    6.536     6.86     7.24 
##      .25      .50      .75      .90      .95 
##     9.55    13.80    18.40    20.94    24.10 
## 
## lowest :  5.6  6.4  6.5  6.9  7.0, highest: 23.1 23.8 26.8 29.5 29.8
## --------------------------------------------------------------------------------
## Non.hispanic.black.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       51        1    10.04    5.814     3.60     4.58 
##      .25      .50      .75      .90      .95 
##     5.90     9.20    12.50    16.34    19.61 
## 
## lowest :  3.0  3.2  3.6  3.7  4.1, highest: 19.4 19.5 20.6 23.7 27.2
## --------------------------------------------------------------------------------
## Non.hispanic.black.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       49        1    7.498    4.843     2.08     2.48 
##      .25      .50      .75      .90      .95 
##     4.20     6.40     9.50    13.14    14.07 
## 
## lowest :  0.9  1.4  1.9  2.1  2.4, highest: 13.5 14.0 14.7 20.3 21.7
## --------------------------------------------------------------------------------
## Non.hispanic.black.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       59     1125       52        1    13.95    7.832     5.49     6.28 
##      .25      .50      .75      .90      .95 
##     8.35    12.90    18.35    23.64    27.61 
## 
## lowest :  4.7  4.8  5.4  5.5  5.6, highest: 26.9 27.5 28.6 29.0 34.2
## --------------------------------------------------------------------------------
## Hispanic.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       55     1129       49        1    7.518    5.006     1.34     1.74 
##      .25      .50      .75      .90      .95 
##     4.55     7.00    10.05    12.42    16.27 
## 
## lowest :  0.3  0.6  1.2  1.4  1.6, highest: 13.2 15.7 17.6 20.0 20.9
## --------------------------------------------------------------------------------
## Hispanic.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       55     1129       42    0.999    5.153     4.24     0.20     0.42 
##      .25      .50      .75      .90      .95 
##     2.35     4.50     7.35     9.48    11.62 
## 
## lowest :  0.0  0.1  0.2  0.3  0.6, highest:  9.6 10.0 10.3 14.7 15.1
## --------------------------------------------------------------------------------
## Hispanic.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       55     1129       46    0.999     12.1    5.692     4.47     6.42 
##      .25      .50      .75      .90      .95 
##     9.65    11.30    13.55    17.56    23.29 
## 
## lowest :  2.1  3.5  4.4  4.5  4.8, highest: 20.4 21.7 27.0 27.2 29.7
## --------------------------------------------------------------------------------
## Asian.or.Pacific.Islander.Prevalence 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       51     1133       46        1    8.796    6.108     2.30     2.60 
##      .25      .50      .75      .90      .95 
##     4.05     7.90    12.10    16.20    19.05 
## 
## lowest :  1.0  2.2  2.4  2.6  2.7, highest: 17.8 19.0 19.1 19.4 21.9
## --------------------------------------------------------------------------------
## Asian.or.Pacific.Islander.Lower.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       51     1133       40    0.999     4.92    4.615     0.40     0.40 
##      .25      .50      .75      .90      .95 
##     1.40     4.60     7.35    11.80    12.50 
## 
## lowest :  0.2  0.3  0.4  0.5  0.6, highest: 11.9 12.3 12.7 13.7 16.0
## --------------------------------------------------------------------------------
## Asian.or.Pacific.Islander.Upper.CI 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##       51     1133       46        1    18.36    7.619     8.30     9.30 
##      .25      .50      .75      .90      .95 
##    12.75    18.30    22.85    26.80    29.90 
## 
## lowest :  7.4  8.0  8.6  8.8  9.3, highest: 28.5 29.8 30.0 30.6 32.0
## --------------------------------------------------------------------------------
## Source_UC 
##        n  missing distinct 
##     1184        0        4 
##                                   
## Value       ADDM  MEDI  NSCH  SPED
## Frequency     59   461    68   596
## Proportion 0.050 0.389 0.057 0.503
## --------------------------------------------------------------------------------
## Source_Full3 
##        n  missing distinct 
##     1184        0        4 
## 
## ADDM Autism & Developmental Disabilities Monitoring Network (59, 0.050), MEDI
## Medicaid (461, 0.389), NSCH National Survey of Children's Health (68, 0.057),
## SPED Special Education Child Count (596, 0.503)
## --------------------------------------------------------------------------------
## Prevalence_Risk2 
##        n  missing distinct 
##     1184        0        2 
##                     
## Value      High  Low
## Frequency   675  509
## Proportion 0.57 0.43
## --------------------------------------------------------------------------------
## Year_Factor 
##        n  missing distinct     Info     Mean      Gmd      .05      .10 
##     1184        0       17    0.996     2008    5.339     2000     2001 
##      .25      .50      .75      .90      .95 
##     2004     2008     2011     2014     2016 
## 
## lowest : 2000 2001 2002 2003 2004, highest: 2012 2013 2014 2015 2016
##                                                                             
## Value       2000  2001  2002  2003  2004  2005  2006  2007  2008  2009  2010
## Frequency     74    67    76    66    73    71    79    74    91    71    78
## Proportion 0.062 0.057 0.064 0.056 0.062 0.060 0.067 0.062 0.077 0.060 0.066
##                                               
## Value       2011  2012  2013  2014  2015  2016
## Frequency     75   114    32    43    37    63
## Proportion 0.063 0.096 0.027 0.036 0.031 0.053
## --------------------------------------------------------------------------------
## Prevalence_Risk4 
##        n  missing distinct 
##     1184        0        4 
##                                                   
## Value           High       Low    Medium Very High
## Frequency        208       509       418        49
## Proportion     0.176     0.430     0.353     0.041
## --------------------------------------------------------------------------------
# The 'basicStats' package provides the 'fBasics' function.

library(fBasics, quietly=TRUE)

# Generate a description of the numeric data.

lapply(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)][,c(2:6, 11:33, 37)], basicStats)
## $Denominator
##                  X...X.i
## nobs        1.184000e+03
## NAs         0.000000e+00
## Minimum     1.016000e+03
## Maximum     5.824922e+06
## 1. Quartile 1.088562e+05
## 3. Quartile 7.826922e+05
## Mean        6.169146e+05
## Median      3.716015e+05
## Sum         7.304269e+08
## SE Mean     2.492806e+04
## LCL Mean    5.680065e+05
## UCL Mean    6.658228e+05
## Variance    7.357476e+11
## Stdev       8.577573e+05
## Skewness    3.404208e+00
## Kurtosis    1.497634e+01
## 
## $Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.500000
## Maximum       37.900000
## 1. Quartile    3.100000
## 3. Quartile    9.200000
## Mean           7.213260
## Median         5.700000
## Sum         8540.500000
## SE Mean        0.165957
## LCL Mean       6.887657
## UCL Mean       7.538863
## Variance      32.609401
## Stdev          5.710464
## Skewness       1.889980
## Kurtosis       4.693481
## 
## $Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.400000
## Maximum       24.900000
## 1. Quartile    3.000000
## 3. Quartile    8.600000
## Mean           6.456926
## Median         5.400000
## Sum         7645.000000
## SE Mean        0.130650
## LCL Mean       6.200594
## UCL Mean       6.713258
## Variance      20.210265
## Stdev          4.495583
## Skewness       1.189909
## Kurtosis       1.267858
## 
## $Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.600000
## Maximum       58.600000
## 1. Quartile    3.400000
## 3. Quartile    9.725000
## Mean           8.260980
## Median         6.000000
## Sum         9781.000000
## SE Mean        0.237095
## LCL Mean       7.795806
## UCL Mean       8.726153
## Variance      66.557445
## Stdev          8.158275
## Skewness       2.948251
## Kurtosis      10.848553
## 
## $Year
##                   X...X.i
## nobs         1.184000e+03
## NAs          0.000000e+00
## Minimum      2.000000e+03
## Maximum      2.016000e+03
## 1. Quartile  2.004000e+03
## 3. Quartile  2.011000e+03
## Mean         2.007582e+03
## Median       2.008000e+03
## Sum          2.376977e+06
## SE Mean      1.348490e-01
## LCL Mean     2.007317e+03
## UCL Mean     2.007846e+03
## Variance     2.153005e+01
## Stdev        4.640049e+00
## Skewness     6.300700e-02
## Kurtosis    -1.042398e+00
## 
## $Numerator_ASD
##                  X...X.i
## nobs        1.184000e+03
## NAs         0.000000e+00
## Minimum     1.100000e+01
## Maximum     7.339400e+04
## 1. Quartile 5.090000e+02
## 3. Quartile 4.211000e+03
## Mean        3.753898e+03
## Median      1.493000e+03
## Sum         4.444615e+06
## SE Mean     1.933588e+02
## LCL Mean    3.374533e+03
## UCL Mean    4.133262e+03
## Variance    4.426695e+07
## Stdev       6.653342e+03
## Skewness    4.940436e+00
## Kurtosis    3.504044e+01
## 
## $Numerator_NonASD
##                  X...X.i
## nobs        1.184000e+03
## NAs         0.000000e+00
## Minimum     9.850000e+02
## Maximum     5.795215e+06
## 1. Quartile 1.084915e+05
## 3. Quartile 7.763330e+05
## Mean        6.131607e+05
## Median      3.702825e+05
## Sum         7.259823e+08
## SE Mean     2.476775e+04
## LCL Mean    5.645671e+05
## UCL Mean    6.617543e+05
## Variance    7.263149e+11
## Stdev       8.522411e+05
## Skewness    3.400574e+00
## Kurtosis    1.493894e+01
## 
## $Proportion
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.000493
## Maximum        0.037577
## 1. Quartile    0.003103
## 3. Quartile    0.009202
## Mean           0.007211
## Median         0.005700
## Sum            8.537509
## SE Mean        0.000166
## LCL Mean       0.006886
## UCL Mean       0.007536
## Variance       0.000033
## Stdev          0.005703
## Skewness       1.883425
## Kurtosis       4.648626
## 
## $Chi_Wilson_Corrected_Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.336464
## Maximum       28.207071
## 1. Quartile    2.936977
## 3. Quartile    8.603390
## Mean           6.534163
## Median         5.376457
## Sum         7736.448940
## SE Mean        0.136429
## LCL Mean       6.266494
## UCL Mean       6.801832
## Variance      22.037488
## Stdev          4.694410
## Skewness       1.343523
## Kurtosis       1.945175
## 
## $Chi_Wilson_Corrected_Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs            0.000000
## Minimum        0.610572
## Maximum       49.762714
## 1. Quartile    3.417054
## 3. Quartile    9.726243
## Mean           8.066799
## Median         6.033234
## Sum         9551.089631
## SE Mean        0.214189
## LCL Mean       7.646566
## UCL Mean       8.487031
## Variance      54.318259
## Stdev          7.370092
## Skewness       2.543562
## Kurtosis       8.114181
## 
## $Male.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        6.800000
## Maximum       39.100000
## 1. Quartile   12.200000
## 3. Quartile   23.100000
## Mean          18.416949
## Median        18.300000
## Sum         1086.600000
## SE Mean        0.988290
## LCL Mean      16.438673
## UCL Mean      20.395226
## Variance      57.626259
## Stdev          7.591196
## Skewness       0.693436
## Kurtosis       0.082172
## 
## $Male.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        5.000000
## Maximum       36.200000
## 1. Quartile   10.600000
## 3. Quartile   20.800000
## Mean          16.230508
## Median        16.100000
## Sum          957.600000
## SE Mean        0.911984
## LCL Mean      14.404975
## UCL Mean      18.056042
## Variance      49.071122
## Stdev          7.005078
## Skewness       0.602089
## Kurtosis      -0.121132
## 
## $Male.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        9.300000
## Maximum       44.900000
## 1. Quartile   14.650000
## 3. Quartile   25.600000
## Mean          20.928814
## Median        20.800000
## Sum         1234.800000
## SE Mean        1.076843
## LCL Mean      18.773278
## UCL Mean      23.084349
## Variance      68.415880
## Stdev          8.271389
## Skewness       0.824592
## Kurtosis       0.432736
## 
## $Female.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        1.500000
## Maximum        9.300000
## 1. Quartile    2.900000
## 3. Quartile    5.500000
## Mean           4.235593
## Median         3.800000
## Sum          249.900000
## SE Mean        0.221212
## LCL Mean       3.792789
## UCL Mean       4.678398
## Variance       2.887160
## Stdev          1.699164
## Skewness       0.661877
## Kurtosis      -0.016958
## 
## $Female.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        0.900000
## Maximum        7.900000
## 1. Quartile    2.050000
## 3. Quartile    4.450000
## Mean           3.249153
## Median         2.900000
## Sum          191.700000
## SE Mean        0.191953
## LCL Mean       2.864916
## UCL Mean       3.633389
## Variance       2.173922
## Stdev          1.474422
## Skewness       0.622519
## Kurtosis      -0.081139
## 
## $Female.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        2.400000
## Maximum       11.600000
## 1. Quartile    3.900000
## 3. Quartile    6.800000
## Mean           5.555932
## Median         5.300000
## Sum          327.800000
## SE Mean        0.264092
## LCL Mean       5.027295
## UCL Mean       6.084569
## Variance       4.114921
## Stdev          2.028527
## Skewness       0.767732
## Kurtosis       0.416455
## 
## $Non.hispanic.white.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        3.800000
## Maximum       26.600000
## 1. Quartile    7.950000
## 3. Quartile   15.650000
## Mean          12.310169
## Median        12.000000
## Sum          726.300000
## SE Mean        0.673193
## LCL Mean      10.962627
## UCL Mean      13.657712
## Variance      26.738171
## Stdev          5.170897
## Skewness       0.472833
## Kurtosis      -0.371644
## 
## $Non.hispanic.white.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        2.600000
## Maximum       24.000000
## 1. Quartile    6.800000
## 3. Quartile   13.850000
## Mean          10.593220
## Median        10.500000
## Sum          625.000000
## SE Mean        0.609356
## LCL Mean       9.373463
## UCL Mean      11.812978
## Variance      21.907539
## Stdev          4.680549
## Skewness       0.388712
## Kurtosis      -0.437977
## 
## $Non.hispanic.white.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        5.600000
## Maximum       29.800000
## 1. Quartile    9.550000
## 3. Quartile   18.400000
## Mean          14.352542
## Median        13.800000
## Sum          846.800000
## SE Mean        0.754133
## LCL Mean      12.842982
## UCL Mean      15.862103
## Variance      33.554261
## Stdev          5.792604
## Skewness       0.626747
## Kurtosis      -0.084953
## 
## $Non.hispanic.black.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        3.000000
## Maximum       27.200000
## 1. Quartile    5.900000
## 3. Quartile   12.500000
## Mean          10.040678
## Median         9.200000
## Sum          592.400000
## SE Mean        0.689413
## LCL Mean       8.660668
## UCL Mean      11.420688
## Variance      28.042110
## Stdev          5.295480
## Skewness       1.014474
## Kurtosis       0.768712
## 
## $Non.hispanic.black.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        0.900000
## Maximum       21.700000
## 1. Quartile    4.200000
## 3. Quartile    9.500000
## Mean           7.498305
## Median         6.400000
## Sum          442.400000
## SE Mean        0.574179
## LCL Mean       6.348961
## UCL Mean       8.647649
## Variance      19.451204
## Stdev          4.410352
## Skewness       0.987988
## Kurtosis       0.946454
## 
## $Non.hispanic.black.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1125.000000
## Minimum        4.700000
## Maximum       34.200000
## 1. Quartile    8.350000
## 3. Quartile   18.350000
## Mean          13.947458
## Median        12.900000
## Sum          822.900000
## SE Mean        0.916070
## LCL Mean      12.113745
## UCL Mean      15.781171
## Variance      49.511847
## Stdev          7.036466
## Skewness       0.843503
## Kurtosis      -0.017762
## 
## $Hispanic.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1129.000000
## Minimum        0.300000
## Maximum       20.900000
## 1. Quartile    4.550000
## 3. Quartile   10.050000
## Mean           7.518182
## Median         7.000000
## Sum          413.500000
## SE Mean        0.612266
## LCL Mean       6.290663
## UCL Mean       8.745701
## Variance      20.617811
## Stdev          4.540684
## Skewness       0.832276
## Kurtosis       0.768377
## 
## $Hispanic.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1129.000000
## Minimum        0.000000
## Maximum       15.100000
## 1. Quartile    2.350000
## 3. Quartile    7.350000
## Mean           5.152727
## Median         4.500000
## Sum          283.400000
## SE Mean        0.510231
## LCL Mean       4.129776
## UCL Mean       6.175679
## Variance      14.318465
## Stdev          3.783975
## Skewness       0.731554
## Kurtosis       0.111254
## 
## $Hispanic.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1129.000000
## Minimum        2.100000
## Maximum       29.700000
## 1. Quartile    9.650000
## 3. Quartile   13.550000
## Mean          12.098182
## Median        11.300000
## Sum          665.400000
## SE Mean        0.734198
## LCL Mean      10.626203
## UCL Mean      13.570161
## Variance      29.647589
## Stdev          5.444960
## Skewness       1.170264
## Kurtosis       2.008961
## 
## $Asian.or.Pacific.Islander.Prevalence
##                 X...X.i
## nobs        1184.000000
## NAs         1133.000000
## Minimum        1.000000
## Maximum       21.900000
## 1. Quartile    4.050000
## 3. Quartile   12.100000
## Mean           8.796078
## Median         7.900000
## Sum          448.600000
## SE Mean        0.751474
## LCL Mean       7.286698
## UCL Mean      10.305459
## Variance      28.800384
## Stdev          5.366599
## Skewness       0.563062
## Kurtosis      -0.639937
## 
## $Asian.or.Pacific.Islander.Lower.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1133.000000
## Minimum        0.200000
## Maximum       16.000000
## 1. Quartile    1.400000
## 3. Quartile    7.350000
## Mean           4.919608
## Median         4.600000
## Sum          250.900000
## SE Mean        0.578755
## LCL Mean       3.757145
## UCL Mean       6.082071
## Variance      17.082808
## Stdev          4.133135
## Skewness       0.781876
## Kurtosis      -0.312861
## 
## $Asian.or.Pacific.Islander.Upper.CI
##                 X...X.i
## nobs        1184.000000
## NAs         1133.000000
## Minimum        7.400000
## Maximum       32.000000
## 1. Quartile   12.750000
## 3. Quartile   22.850000
## Mean          18.364706
## Median        18.300000
## Sum          936.600000
## SE Mean        0.924256
## LCL Mean      16.508283
## UCL Mean      20.221129
## Variance      43.566729
## Stdev          6.600510
## Skewness       0.146689
## Kurtosis      -0.871149
## 
## $Year_Factor
##                   X...X.i
## nobs         1.184000e+03
## NAs          0.000000e+00
## Minimum      2.000000e+03
## Maximum      2.016000e+03
## 1. Quartile  2.004000e+03
## 3. Quartile  2.011000e+03
## Mean         2.007582e+03
## Median       2.008000e+03
## Sum          2.376977e+06
## SE Mean      1.348490e-01
## LCL Mean     2.007317e+03
## UCL Mean     2.007846e+03
## Variance     2.153005e+01
## Stdev        4.640049e+00
## Skewness     6.300700e-02
## Kurtosis    -1.042398e+00
# The 'kurtosis' package provides the 'fBasics' function.

library(fBasics, quietly=TRUE)

# Summarise the kurtosis of the numeric data.

kurtosis(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)][,c(2:6, 11:33, 37)], na.rm=TRUE)
##                          Denominator                           Prevalence 
##                          14.97634215                           4.69348071 
##                             Lower.CI                             Upper.CI 
##                           1.26785795                          10.84855328 
##                                 Year                        Numerator_ASD 
##                          -1.04239762                          35.04043901 
##                     Numerator_NonASD                           Proportion 
##                          14.93894416                           4.64862578 
##        Chi_Wilson_Corrected_Lower.CI        Chi_Wilson_Corrected_Upper.CI 
##                           1.94517471                           8.11418140 
##                      Male.Prevalence                        Male.Lower.CI 
##                           0.08217208                          -0.12113172 
##                        Male.Upper.CI                    Female.Prevalence 
##                           0.43273587                          -0.01695817 
##                      Female.Lower.CI                      Female.Upper.CI 
##                          -0.08113894                           0.41645459 
##        Non.hispanic.white.Prevalence          Non.hispanic.white.Lower.CI 
##                          -0.37164379                          -0.43797703 
##          Non.hispanic.white.Upper.CI        Non.hispanic.black.Prevalence 
##                          -0.08495331                           0.76871187 
##          Non.hispanic.black.Lower.CI          Non.hispanic.black.Upper.CI 
##                           0.94645425                          -0.01776160 
##                  Hispanic.Prevalence                    Hispanic.Lower.CI 
##                           0.76837749                           0.11125366 
##                    Hispanic.Upper.CI Asian.or.Pacific.Islander.Prevalence 
##                           2.00896110                          -0.63993651 
##   Asian.or.Pacific.Islander.Lower.CI   Asian.or.Pacific.Islander.Upper.CI 
##                          -0.31286138                          -0.87114887 
##                          Year_Factor 
##                          -1.04239762
# The 'skewness' package provides the 'fBasics' function.

library(fBasics, quietly=TRUE)

# Summarise the skewness of the numeric data.

skewness(crs$dataset[crs$train, c(crs$input, crs$risk, crs$target)][,c(2:6, 11:33, 37)], na.rm=TRUE)
##                          Denominator                           Prevalence 
##                           3.40420823                           1.88998047 
##                             Lower.CI                             Upper.CI 
##                           1.18990869                           2.94825104 
##                                 Year                        Numerator_ASD 
##                           0.06300733                           4.94043621 
##                     Numerator_NonASD                           Proportion 
##                           3.40057399                           1.88342452 
##        Chi_Wilson_Corrected_Lower.CI        Chi_Wilson_Corrected_Upper.CI 
##                           1.34352272                           2.54356199 
##                      Male.Prevalence                        Male.Lower.CI 
##                           0.69343578                           0.60208943 
##                        Male.Upper.CI                    Female.Prevalence 
##                           0.82459165                           0.66187701 
##                      Female.Lower.CI                      Female.Upper.CI 
##                           0.62251878                           0.76773164 
##        Non.hispanic.white.Prevalence          Non.hispanic.white.Lower.CI 
##                           0.47283284                           0.38871201 
##          Non.hispanic.white.Upper.CI        Non.hispanic.black.Prevalence 
##                           0.62674688                           1.01447403 
##          Non.hispanic.black.Lower.CI          Non.hispanic.black.Upper.CI 
##                           0.98798810                           0.84350272 
##                  Hispanic.Prevalence                    Hispanic.Lower.CI 
##                           0.83227557                           0.73155432 
##                    Hispanic.Upper.CI Asian.or.Pacific.Islander.Prevalence 
##                           1.17026436                           0.56306152 
##   Asian.or.Pacific.Islander.Lower.CI   Asian.or.Pacific.Islander.Upper.CI 
##                           0.78187593                           0.14668871 
##                          Year_Factor 
##                           0.06300733
# The 'mice' package provides the 'md.pattern' function.

library(mice, quietly=TRUE)

# Generate a summary of the missing values in the dataset.

md.pattern(crs$dataset[,c(crs$input, crs$target)])

##      State Denominator Prevalence Lower.CI Upper.CI Year Source Source_Full1
## 68       1           1          1        1        1    1      1            1
## 9        1           1          1        1        1    1      1            1
## 8        1           1          1        1        1    1      1            1
## 1        1           1          1        1        1    1      1            1
## 1606     1           1          1        1        1    1      1            1
##          0           0          0        0        0    0      0            0
##      State_Full1 State_Full2 Numerator_ASD Numerator_NonASD Proportion
## 68             1           1             1                1          1
## 9              1           1             1                1          1
## 8              1           1             1                1          1
## 1              1           1             1                1          1
## 1606           1           1             1                1          1
##                0           0             0                0          0
##      Chi_Wilson_Corrected_Lower.CI Chi_Wilson_Corrected_Upper.CI Source_UC
## 68                               1                             1         1
## 9                                1                             1         1
## 8                                1                             1         1
## 1                                1                             1         1
## 1606                             1                             1         1
##                                  0                             0         0
##      Source_Full3 Prevalence_Risk2 Year_Factor Prevalence_Risk4 Male.Prevalence
## 68              1                1           1                1               1
## 9               1                1           1                1               1
## 8               1                1           1                1               1
## 1               1                1           1                1               1
## 1606            1                1           1                1               0
##                 0                0           0                0            1606
##      Male.Lower.CI Male.Upper.CI Female.Prevalence Female.Lower.CI
## 68               1             1                 1               1
## 9                1             1                 1               1
## 8                1             1                 1               1
## 1                1             1                 1               1
## 1606             0             0                 0               0
##               1606          1606              1606            1606
##      Female.Upper.CI Non.hispanic.white.Prevalence Non.hispanic.white.Lower.CI
## 68                 1                             1                           1
## 9                  1                             1                           1
## 8                  1                             1                           1
## 1                  1                             1                           1
## 1606               0                             0                           0
##                 1606                          1606                        1606
##      Non.hispanic.white.Upper.CI Non.hispanic.black.Prevalence
## 68                             1                             1
## 9                              1                             1
## 8                              1                             1
## 1                              1                             0
## 1606                           0                             0
##                             1606                          1607
##      Non.hispanic.black.Lower.CI Non.hispanic.black.Upper.CI
## 68                             1                           1
## 9                              1                           1
## 8                              1                           1
## 1                              0                           0
## 1606                           0                           0
##                             1607                        1607
##      Hispanic.Prevalence Hispanic.Lower.CI Hispanic.Upper.CI
## 68                     1                 1                 1
## 9                      1                 1                 1
## 8                      0                 0                 0
## 1                      0                 0                 0
## 1606                   0                 0                 0
##                     1615              1615              1615
##      Asian.or.Pacific.Islander.Prevalence Asian.or.Pacific.Islander.Lower.CI
## 68                                      1                                  1
## 9                                       0                                  0
## 8                                       0                                  0
## 1                                       0                                  0
## 1606                                    0                                  0
##                                      1624                               1624
##      Asian.or.Pacific.Islander.Upper.CI      
## 68                                    1     0
## 9                                     0     3
## 8                                     0     6
## 1                                     0     9
## 1606                                  0    18
##                                    1624 28992
# The 'CrossTable' package provides the 'descr' function.

library(descr, quietly=TRUE)

# Generate cross tabulations for categoric data.

for (i in c(1, 7:10, 34:36)) 
{ 
  cat(sprintf('CrossTab of %s by target variable %s\n\n', names(crs$dataset)[i], crs$target)) 
  print(CrossTable(crs$dataset[[i]], crs$dataset[[crs$target]], expected=TRUE, format='SAS')) 
  cat(paste(rep('=', 70), collapse=''), '

') 
}
## CrossTab of State by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ================================================================
##                     crs$dataset[[crs$target]]
## crs$dataset[[i]]      High      Low   Medium   Very High   Total
## ----------------------------------------------------------------
## AK                       2       14       14           2      32
##                        5.6     14.0     11.0         1.4        
##                      2.280    0.000    0.791       0.258        
##                      0.062    0.438    0.438       0.062   0.019
##                      0.007    0.019    0.024       0.027        
##                      0.001    0.008    0.008       0.001        
## ----------------------------------------------------------------
## AL                       6       17        9           4      36
##                        6.3     15.7     12.4         1.6        
##                      0.010    0.100    0.944       3.737        
##                      0.167    0.472    0.250       0.111   0.021
##                      0.020    0.023    0.015       0.054        
##                      0.004    0.010    0.005       0.002        
## ----------------------------------------------------------------
## AR                       4       13       19           1      37
##                        6.4     16.2     12.8         1.6        
##                      0.918    0.626    3.039       0.236        
##                      0.108    0.351    0.514       0.027   0.022
##                      0.014    0.018    0.033       0.014        
##                      0.002    0.008    0.011       0.001        
## ----------------------------------------------------------------
## AZ                      10       14       15           1      40
##                        7.0     17.5     13.8         1.7        
##                      1.338    0.698    0.103       0.321        
##                      0.250    0.350    0.375       0.025   0.024
##                      0.034    0.019    0.026       0.014        
##                      0.006    0.008    0.009       0.001        
## ----------------------------------------------------------------
## CA                       6       18        7           0      31
##                        5.4     13.6     10.7         1.4        
##                      0.070    1.455    1.279       1.356        
##                      0.194    0.581    0.226       0.000   0.018
##                      0.020    0.024    0.012       0.000        
##                      0.004    0.011    0.004       0.000        
## ----------------------------------------------------------------
## CO                       4       21       12           0      37
##                        6.4     16.2     12.8         1.6        
##                      0.918    1.434    0.047       1.618        
##                      0.108    0.568    0.324       0.000   0.022
##                      0.014    0.028    0.021       0.000        
##                      0.002    0.012    0.007       0.000        
## ----------------------------------------------------------------
## CT                       9       14        9           1      33
##                        5.7     14.4     11.4         1.4        
##                      1.860    0.013    0.502       0.136        
##                      0.273    0.424    0.273       0.030   0.020
##                      0.031    0.019    0.015       0.014        
##                      0.005    0.008    0.005       0.001        
## ----------------------------------------------------------------
## DC                       3       15        7           0      25
##                        4.3     10.9      8.6         1.1        
##                      0.416    1.512    0.307       1.093        
##                      0.120    0.600    0.280       0.000   0.015
##                      0.010    0.020    0.012       0.000        
##                      0.002    0.009    0.004       0.000        
## ----------------------------------------------------------------
## DE                       3       17       10           2      32
##                        5.6     14.0     11.0         1.4        
##                      1.179    0.645    0.099       0.258        
##                      0.094    0.531    0.312       0.062   0.019
##                      0.010    0.023    0.017       0.027        
##                      0.002    0.010    0.006       0.001        
## ----------------------------------------------------------------
## FL                       4       20        9           1      34
##                        5.9     14.9     11.7         1.5        
##                      0.616    1.770    0.638       0.159        
##                      0.118    0.588    0.265       0.029   0.020
##                      0.014    0.027    0.015       0.014        
##                      0.002    0.012    0.005       0.001        
## ----------------------------------------------------------------
## GA                       6       15       17           1      39
##                        6.8     17.1     13.5         1.7        
##                      0.089    0.248    0.930       0.292        
##                      0.154    0.385    0.436       0.026   0.023
##                      0.020    0.020    0.029       0.014        
##                      0.004    0.009    0.010       0.001        
## ----------------------------------------------------------------
## HI                       1       19       11           0      31
##                        5.4     13.6     10.7         1.4        
##                      3.572    2.184    0.008       1.356        
##                      0.032    0.613    0.355       0.000   0.018
##                      0.003    0.026    0.019       0.000        
##                      0.001    0.011    0.007       0.000        
## ----------------------------------------------------------------
## IA                       2       23        6           1      32
##                        5.6     14.0     11.0         1.4        
##                      2.280    5.794    2.304       0.114        
##                      0.062    0.719    0.188       0.031   0.019
##                      0.007    0.031    0.010       0.014        
##                      0.001    0.014    0.004       0.001        
## ----------------------------------------------------------------
## ID                       5        8       14           5      32
##                        5.6     14.0     11.0         1.4        
##                      0.056    2.568    0.791       9.263        
##                      0.156    0.250    0.438       0.156   0.019
##                      0.017    0.011    0.024       0.068        
##                      0.003    0.005    0.008       0.003        
## ----------------------------------------------------------------
## IL                       2       16       12           2      32
##                        5.6     14.0     11.0         1.4        
##                      2.280    0.287    0.083       0.258        
##                      0.062    0.500    0.375       0.062   0.019
##                      0.007    0.022    0.021       0.027        
##                      0.001    0.009    0.007       0.001        
## ----------------------------------------------------------------
## IN                       9        9       13           2      33
##                        5.7     14.4     11.4         1.4        
##                      1.860    2.045    0.228       0.215        
##                      0.273    0.273    0.394       0.061   0.020
##                      0.031    0.012    0.022       0.027        
##                      0.005    0.005    0.008       0.001        
## ----------------------------------------------------------------
## KS                       1       14       15           0      30
##                        5.2     13.1     10.4         1.3        
##                      3.405    0.059    2.084       1.312        
##                      0.033    0.467    0.500       0.000   0.018
##                      0.003    0.019    0.026       0.000        
##                      0.001    0.008    0.009       0.000        
## ----------------------------------------------------------------
## KY                       2       17       11           2      32
##                        5.6     14.0     11.0         1.4        
##                      2.280    0.645    0.000       0.258        
##                      0.062    0.531    0.344       0.062   0.019
##                      0.007    0.023    0.019       0.027        
##                      0.001    0.010    0.007       0.001        
## ----------------------------------------------------------------
## LA                       1       24        6           1      32
##                        5.6     14.0     11.0         1.4        
##                      3.740    7.152    2.304       0.114        
##                      0.031    0.750    0.188       0.031   0.019
##                      0.003    0.032    0.010       0.014        
##                      0.001    0.014    0.004       0.001        
## ----------------------------------------------------------------
## MA                       9       15        7           2      33
##                        5.7     14.4     11.4         1.4        
##                      1.860    0.022    1.692       0.215        
##                      0.273    0.455    0.212       0.061   0.020
##                      0.031    0.020    0.012       0.027        
##                      0.005    0.009    0.004       0.001        
## ----------------------------------------------------------------
## MD                      10        9       19           2      40
##                        7.0     17.5     13.8         1.7        
##                      1.338    4.124    1.954       0.036        
##                      0.250    0.225    0.475       0.050   0.024
##                      0.034    0.012    0.033       0.027        
##                      0.006    0.005    0.011       0.001        
## ----------------------------------------------------------------
## ME                      12        4        6           5      27
##                        4.7     11.8      9.3         1.2        
##                     11.385    5.163    1.182      12.352        
##                      0.444    0.148    0.222       0.185   0.016
##                      0.041    0.005    0.010       0.068        
##                      0.007    0.002    0.004       0.003        
## ----------------------------------------------------------------
## MI                       6        5       20           1      32
##                        5.6     14.0     11.0         1.4        
##                      0.035    5.782    7.261       0.114        
##                      0.188    0.156    0.625       0.031   0.019
##                      0.020    0.007    0.034       0.014        
##                      0.004    0.003    0.012       0.001        
## ----------------------------------------------------------------
## MN                      21        2        8           3      34
##                        5.9     14.9     11.7         1.5        
##                     38.555   11.139    1.189       1.539        
##                      0.618    0.059    0.235       0.088   0.020
##                      0.071    0.003    0.014       0.041        
##                      0.012    0.001    0.005       0.002        
## ----------------------------------------------------------------
## MO                      10       12       15           2      39
##                        6.8     17.1     13.5         1.7        
##                      1.533    1.499    0.176       0.051        
##                      0.256    0.308    0.385       0.051   0.023
##                      0.034    0.016    0.026       0.027        
##                      0.006    0.007    0.009       0.001        
## ----------------------------------------------------------------
## MS                       0       22        8           0      30
##                        5.2     13.1     10.4         1.3        
##                      5.213    6.009    0.535       1.312        
##                      0.000    0.733    0.267       0.000   0.018
##                      0.000    0.030    0.014       0.000        
##                      0.000    0.013    0.005       0.000        
## ----------------------------------------------------------------
## MT                       7       13        7           2      29
##                        5.0     12.7     10.0         1.3        
##                      0.763    0.008    0.905       0.422        
##                      0.241    0.448    0.241       0.069   0.017
##                      0.024    0.018    0.012       0.027        
##                      0.004    0.008    0.004       0.001        
## ----------------------------------------------------------------
## NC                       9       12       17           1      39
##                        6.8     17.1     13.5         1.7        
##                      0.729    1.499    0.930       0.292        
##                      0.231    0.308    0.436       0.026   0.023
##                      0.031    0.016    0.029       0.014        
##                      0.005    0.007    0.010       0.001        
## ----------------------------------------------------------------
## ND                       8       11       12           0      31
##                        5.4     13.6     10.7         1.4        
##                      1.268    0.483    0.158       1.356        
##                      0.258    0.355    0.387       0.000   0.018
##                      0.027    0.015    0.021       0.000        
##                      0.005    0.007    0.007       0.000        
## ----------------------------------------------------------------
## NE                       3       21        7           0      31
##                        5.4     13.6     10.7         1.4        
##                      1.057    4.085    1.279       1.356        
##                      0.097    0.677    0.226       0.000   0.018
##                      0.010    0.028    0.012       0.000        
##                      0.002    0.012    0.004       0.000        
## ----------------------------------------------------------------
## NH                      13        9       10           1      33
##                        5.7     14.4     11.4         1.4        
##                      9.207    2.045    0.170       0.136        
##                      0.394    0.273    0.303       0.030   0.020
##                      0.044    0.012    0.017       0.014        
##                      0.008    0.005    0.006       0.001        
## ----------------------------------------------------------------
## NJ                       7       13       12           6      38
##                        6.6     16.6     13.1         1.7        
##                      0.024    0.788    0.095      11.323        
##                      0.184    0.342    0.316       0.158   0.022
##                      0.024    0.018    0.021       0.081        
##                      0.004    0.008    0.007       0.004        
## ----------------------------------------------------------------
## NM                       0       23        7           0      30
##                        5.2     13.1     10.4         1.3        
##                      5.213    7.439    1.087       1.312        
##                      0.000    0.767    0.233       0.000   0.018
##                      0.000    0.031    0.012       0.000        
##                      0.000    0.014    0.004       0.000        
## ----------------------------------------------------------------
## NV                       3       19        9           1      32
##                        5.6     14.0     11.0         1.4        
##                      1.179    1.790    0.379       0.114        
##                      0.094    0.594    0.281       0.031   0.019
##                      0.010    0.026    0.015       0.014        
##                      0.002    0.011    0.005       0.001        
## ----------------------------------------------------------------
## NY                       5       16       11           1      33
##                        5.7     14.4     11.4         1.4        
##                      0.094    0.170    0.013       0.136        
##                      0.152    0.485    0.333       0.030   0.020
##                      0.017    0.022    0.019       0.014        
##                      0.003    0.009    0.007       0.001        
## ----------------------------------------------------------------
## OH                       5       15       10           1      31
##                        5.4     13.6     10.7         1.4        
##                      0.028    0.153    0.046       0.093        
##                      0.161    0.484    0.323       0.032   0.018
##                      0.017    0.020    0.017       0.014        
##                      0.003    0.009    0.006       0.001        
## ----------------------------------------------------------------
## OK                       2       20       10           1      33
##                        5.7     14.4     11.4         1.4        
##                      2.432    2.148    0.170       0.136        
##                      0.061    0.606    0.303       0.030   0.020
##                      0.007    0.027    0.017       0.014        
##                      0.001    0.012    0.006       0.001        
## ----------------------------------------------------------------
## OR                      12        2       18           2      34
##                        5.9     14.9     11.7         1.5        
##                      6.282   11.139    3.344       0.177        
##                      0.353    0.059    0.529       0.059   0.020
##                      0.041    0.003    0.031       0.027        
##                      0.007    0.001    0.011       0.001        
## ----------------------------------------------------------------
## PA                       9       14       11           2      36
##                        6.3     15.7     12.4         1.6        
##                      1.204    0.193    0.164       0.115        
##                      0.250    0.389    0.306       0.056   0.021
##                      0.031    0.019    0.019       0.027        
##                      0.005    0.008    0.007       0.001        
## ----------------------------------------------------------------
## RI                      16        6        9           2      33
##                        5.7     14.4     11.4         1.4        
##                     18.380    4.927    0.502       0.215        
##                      0.485    0.182    0.273       0.061   0.020
##                      0.054    0.008    0.015       0.027        
##                      0.009    0.004    0.005       0.001        
## ----------------------------------------------------------------
## SC                       3       17       17           1      38
##                        6.6     16.6     13.1         1.7        
##                      1.966    0.009    1.150       0.264        
##                      0.079    0.447    0.447       0.026   0.022
##                      0.010    0.023    0.029       0.014        
##                      0.002    0.010    0.010       0.001        
## ----------------------------------------------------------------
## SD                       1       23        7           0      31
##                        5.4     13.6     10.7         1.4        
##                      3.572    6.576    1.279       1.356        
##                      0.032    0.742    0.226       0.000   0.018
##                      0.003    0.031    0.012       0.000        
##                      0.001    0.014    0.004       0.000        
## ----------------------------------------------------------------
## TN                       2       20       10           1      33
##                        5.7     14.4     11.4         1.4        
##                      2.432    2.148    0.170       0.136        
##                      0.061    0.606    0.303       0.030   0.020
##                      0.007    0.027    0.017       0.014        
##                      0.001    0.012    0.006       0.001        
## ----------------------------------------------------------------
## TX                       1       21        8           0      30
##                        5.2     13.1     10.4         1.3        
##                      3.405    4.732    0.535       1.312        
##                      0.033    0.700    0.267       0.000   0.018
##                      0.003    0.028    0.014       0.000        
##                      0.001    0.012    0.005       0.000        
## ----------------------------------------------------------------
## UT                       3       17       14           2      36
##                        6.3     15.7     12.4         1.6        
##                      1.694    0.100    0.200       0.115        
##                      0.083    0.472    0.389       0.056   0.021
##                      0.010    0.023    0.024       0.027        
##                      0.002    0.010    0.008       0.001        
## ----------------------------------------------------------------
## VA                       8       15        8           1      32
##                        5.6     14.0     11.0         1.4        
##                      1.070    0.072    0.839       0.114        
##                      0.250    0.469    0.250       0.031   0.019
##                      0.027    0.020    0.014       0.014        
##                      0.005    0.009    0.005       0.001        
## ----------------------------------------------------------------
## VT                      10        7        9           4      30
##                        5.2     13.1     10.4         1.3        
##                      4.396    2.855    0.177       5.507        
##                      0.333    0.233    0.300       0.133   0.018
##                      0.034    0.009    0.015       0.054        
##                      0.006    0.004    0.005       0.002        
## ----------------------------------------------------------------
## WA                       3       19        9           1      32
##                        5.6     14.0     11.0         1.4        
##                      1.179    1.790    0.379       0.114        
##                      0.094    0.594    0.281       0.031   0.019
##                      0.010    0.026    0.015       0.014        
##                      0.002    0.011    0.005       0.001        
## ----------------------------------------------------------------
## WI                       9        5       24           1      39
##                        6.8     17.1     13.5         1.7        
##                      0.729    8.522    8.251       0.292        
##                      0.231    0.128    0.615       0.026   0.023
##                      0.031    0.007    0.041       0.014        
##                      0.005    0.003    0.014       0.001        
## ----------------------------------------------------------------
## WV                       5       12       15           2      34
##                        5.9     14.9     11.7         1.5        
##                      0.139    0.554    0.908       0.177        
##                      0.147    0.353    0.441       0.059   0.020
##                      0.017    0.016    0.026       0.027        
##                      0.003    0.007    0.009       0.001        
## ----------------------------------------------------------------
## WY                       2       13       14           0      29
##                        5.0     12.7     10.0         1.3        
##                      1.833    0.008    1.591       1.268        
##                      0.069    0.448    0.483       0.000   0.017
##                      0.007    0.018    0.024       0.000        
##                      0.001    0.008    0.008       0.000        
## ----------------------------------------------------------------
## Total                  294      740      584          74    1692
##                      0.174    0.437    0.345       0.044        
## ================================================================
## ====================================================================== 
## 
## CrossTab of Source by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ================================================================
##                     crs$dataset[[crs$target]]
## crs$dataset[[i]]      High      Low   Medium   Very High   Total
## ----------------------------------------------------------------
## addm                    38        5       36           7      86
##                       14.9     37.6     29.7         3.8        
##                     35.575   28.277    1.344       2.789        
##                      0.442    0.058    0.419       0.081   0.051
##                      0.129    0.007    0.062       0.095        
##                      0.022    0.003    0.021       0.004        
## ----------------------------------------------------------------
## medi                    74      344      225          12     655
##                      113.8    286.5    226.1        28.6        
##                     13.926   11.555    0.005       9.673        
##                      0.113    0.525    0.344       0.018   0.387
##                      0.252    0.465    0.385       0.162        
##                      0.044    0.203    0.133       0.007        
## ----------------------------------------------------------------
## nsch                    38        0        5          55      98
##                       17.0     42.9     33.8         4.3        
##                     25.828   42.861   24.564     600.064        
##                      0.388    0.000    0.051       0.561   0.058
##                      0.129    0.000    0.009       0.743        
##                      0.022    0.000    0.003       0.033        
## ----------------------------------------------------------------
## sped                   144      391      318           0     853
##                      148.2    373.1    294.4        37.3        
##                      0.120    0.863    1.889      37.306        
##                      0.169    0.458    0.373       0.000   0.504
##                      0.490    0.528    0.545       0.000        
##                      0.085    0.231    0.188       0.000        
## ----------------------------------------------------------------
## Total                  294      740      584          74    1692
##                      0.174    0.437    0.345       0.044        
## ================================================================
## ====================================================================== 
## 
## CrossTab of Source_Full1 by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ================================================================================
##                                crs$dataset[[crs$target]]
## crs$dataset[[i]]                  High       Low    Medium   Very High     Total
## --------------------------------------------------------------------------------
## Atsm & Dvlpmntl Dsblts Mn N         38         5        36           7        86
##                                   14.9      37.6      29.7         3.8          
##                                 35.575    28.277     1.344       2.789          
##                                  0.442     0.058     0.419       0.081     0.051
##                                  0.129     0.007     0.062       0.095          
##                                  0.022     0.003     0.021       0.004          
## --------------------------------------------------------------------------------
## Medicaid                            74       344       225          12       655
##                                  113.8     286.5     226.1        28.6          
##                                 13.926    11.555     0.005       9.673          
##                                  0.113     0.525     0.344       0.018     0.387
##                                  0.252     0.465     0.385       0.162          
##                                  0.044     0.203     0.133       0.007          
## --------------------------------------------------------------------------------
## Natnl Srvy of Chldrn's Hlth         38         0         5          55        98
##                                   17.0      42.9      33.8         4.3          
##                                 25.828    42.861    24.564     600.064          
##                                  0.388     0.000     0.051       0.561     0.058
##                                  0.129     0.000     0.009       0.743          
##                                  0.022     0.000     0.003       0.033          
## --------------------------------------------------------------------------------
## Special Education Child Cnt        144       391       318           0       853
##                                  148.2     373.1     294.4        37.3          
##                                  0.120     0.863     1.889      37.306          
##                                  0.169     0.458     0.373       0.000     0.504
##                                  0.490     0.528     0.545       0.000          
##                                  0.085     0.231     0.188       0.000          
## --------------------------------------------------------------------------------
## Total                              294       740       584          74      1692
##                                  0.174     0.437     0.345       0.044          
## ================================================================================
## ====================================================================== 
## 
## CrossTab of State_Full1 by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ====================================================================
##                         crs$dataset[[crs$target]]
## crs$dataset[[i]]          High      Low   Medium   Very High   Total
## --------------------------------------------------------------------
## Alabama                      6       17        9           4      36
##                            6.3     15.7     12.4         1.6        
##                          0.010    0.100    0.944       3.737        
##                          0.167    0.472    0.250       0.111   0.021
##                          0.020    0.023    0.015       0.054        
##                          0.004    0.010    0.005       0.002        
## --------------------------------------------------------------------
## Alaska                       2       14       14           2      32
##                            5.6     14.0     11.0         1.4        
##                          2.280    0.000    0.791       0.258        
##                          0.062    0.438    0.438       0.062   0.019
##                          0.007    0.019    0.024       0.027        
##                          0.001    0.008    0.008       0.001        
## --------------------------------------------------------------------
## Arizona                     10       14       15           1      40
##                            7.0     17.5     13.8         1.7        
##                          1.338    0.698    0.103       0.321        
##                          0.250    0.350    0.375       0.025   0.024
##                          0.034    0.019    0.026       0.014        
##                          0.006    0.008    0.009       0.001        
## --------------------------------------------------------------------
## Arkansas                     4       13       19           1      37
##                            6.4     16.2     12.8         1.6        
##                          0.918    0.626    3.039       0.236        
##                          0.108    0.351    0.514       0.027   0.022
##                          0.014    0.018    0.033       0.014        
##                          0.002    0.008    0.011       0.001        
## --------------------------------------------------------------------
## California                   6       18        7           0      31
##                            5.4     13.6     10.7         1.4        
##                          0.070    1.455    1.279       1.356        
##                          0.194    0.581    0.226       0.000   0.018
##                          0.020    0.024    0.012       0.000        
##                          0.004    0.011    0.004       0.000        
## --------------------------------------------------------------------
## Colorado                     4       21       12           0      37
##                            6.4     16.2     12.8         1.6        
##                          0.918    1.434    0.047       1.618        
##                          0.108    0.568    0.324       0.000   0.022
##                          0.014    0.028    0.021       0.000        
##                          0.002    0.012    0.007       0.000        
## --------------------------------------------------------------------
## Connecticut                  9       14        9           1      33
##                            5.7     14.4     11.4         1.4        
##                          1.860    0.013    0.502       0.136        
##                          0.273    0.424    0.273       0.030   0.020
##                          0.031    0.019    0.015       0.014        
##                          0.005    0.008    0.005       0.001        
## --------------------------------------------------------------------
## Delaware                     3       17       10           2      32
##                            5.6     14.0     11.0         1.4        
##                          1.179    0.645    0.099       0.258        
##                          0.094    0.531    0.312       0.062   0.019
##                          0.010    0.023    0.017       0.027        
##                          0.002    0.010    0.006       0.001        
## --------------------------------------------------------------------
## District of Columbia         3       15        7           0      25
##                            4.3     10.9      8.6         1.1        
##                          0.416    1.512    0.307       1.093        
##                          0.120    0.600    0.280       0.000   0.015
##                          0.010    0.020    0.012       0.000        
##                          0.002    0.009    0.004       0.000        
## --------------------------------------------------------------------
## Florida                      4       20        9           1      34
##                            5.9     14.9     11.7         1.5        
##                          0.616    1.770    0.638       0.159        
##                          0.118    0.588    0.265       0.029   0.020
##                          0.014    0.027    0.015       0.014        
##                          0.002    0.012    0.005       0.001        
## --------------------------------------------------------------------
## Georgia                      6       15       17           1      39
##                            6.8     17.1     13.5         1.7        
##                          0.089    0.248    0.930       0.292        
##                          0.154    0.385    0.436       0.026   0.023
##                          0.020    0.020    0.029       0.014        
##                          0.004    0.009    0.010       0.001        
## --------------------------------------------------------------------
## Hawaii                       1       19       11           0      31
##                            5.4     13.6     10.7         1.4        
##                          3.572    2.184    0.008       1.356        
##                          0.032    0.613    0.355       0.000   0.018
##                          0.003    0.026    0.019       0.000        
##                          0.001    0.011    0.007       0.000        
## --------------------------------------------------------------------
## Idaho                        5        8       14           5      32
##                            5.6     14.0     11.0         1.4        
##                          0.056    2.568    0.791       9.263        
##                          0.156    0.250    0.438       0.156   0.019
##                          0.017    0.011    0.024       0.068        
##                          0.003    0.005    0.008       0.003        
## --------------------------------------------------------------------
## Illinois                     2       16       12           2      32
##                            5.6     14.0     11.0         1.4        
##                          2.280    0.287    0.083       0.258        
##                          0.062    0.500    0.375       0.062   0.019
##                          0.007    0.022    0.021       0.027        
##                          0.001    0.009    0.007       0.001        
## --------------------------------------------------------------------
## Indiana                      9        9       13           2      33
##                            5.7     14.4     11.4         1.4        
##                          1.860    2.045    0.228       0.215        
##                          0.273    0.273    0.394       0.061   0.020
##                          0.031    0.012    0.022       0.027        
##                          0.005    0.005    0.008       0.001        
## --------------------------------------------------------------------
## Iowa                         2       23        6           1      32
##                            5.6     14.0     11.0         1.4        
##                          2.280    5.794    2.304       0.114        
##                          0.062    0.719    0.188       0.031   0.019
##                          0.007    0.031    0.010       0.014        
##                          0.001    0.014    0.004       0.001        
## --------------------------------------------------------------------
## Kansas                       1       14       15           0      30
##                            5.2     13.1     10.4         1.3        
##                          3.405    0.059    2.084       1.312        
##                          0.033    0.467    0.500       0.000   0.018
##                          0.003    0.019    0.026       0.000        
##                          0.001    0.008    0.009       0.000        
## --------------------------------------------------------------------
## Kentucky                     2       17       11           2      32
##                            5.6     14.0     11.0         1.4        
##                          2.280    0.645    0.000       0.258        
##                          0.062    0.531    0.344       0.062   0.019
##                          0.007    0.023    0.019       0.027        
##                          0.001    0.010    0.007       0.001        
## --------------------------------------------------------------------
## Louisiana                    1       24        6           1      32
##                            5.6     14.0     11.0         1.4        
##                          3.740    7.152    2.304       0.114        
##                          0.031    0.750    0.188       0.031   0.019
##                          0.003    0.032    0.010       0.014        
##                          0.001    0.014    0.004       0.001        
## --------------------------------------------------------------------
## Maine                       12        4        6           5      27
##                            4.7     11.8      9.3         1.2        
##                         11.385    5.163    1.182      12.352        
##                          0.444    0.148    0.222       0.185   0.016
##                          0.041    0.005    0.010       0.068        
##                          0.007    0.002    0.004       0.003        
## --------------------------------------------------------------------
## Maryland                    10        9       19           2      40
##                            7.0     17.5     13.8         1.7        
##                          1.338    4.124    1.954       0.036        
##                          0.250    0.225    0.475       0.050   0.024
##                          0.034    0.012    0.033       0.027        
##                          0.006    0.005    0.011       0.001        
## --------------------------------------------------------------------
## Massachusetts                9       15        7           2      33
##                            5.7     14.4     11.4         1.4        
##                          1.860    0.022    1.692       0.215        
##                          0.273    0.455    0.212       0.061   0.020
##                          0.031    0.020    0.012       0.027        
##                          0.005    0.009    0.004       0.001        
## --------------------------------------------------------------------
## Michigan                     6        5       20           1      32
##                            5.6     14.0     11.0         1.4        
##                          0.035    5.782    7.261       0.114        
##                          0.188    0.156    0.625       0.031   0.019
##                          0.020    0.007    0.034       0.014        
##                          0.004    0.003    0.012       0.001        
## --------------------------------------------------------------------
## Minnesota                   21        2        8           3      34
##                            5.9     14.9     11.7         1.5        
##                         38.555   11.139    1.189       1.539        
##                          0.618    0.059    0.235       0.088   0.020
##                          0.071    0.003    0.014       0.041        
##                          0.012    0.001    0.005       0.002        
## --------------------------------------------------------------------
## Mississippi                  0       22        8           0      30
##                            5.2     13.1     10.4         1.3        
##                          5.213    6.009    0.535       1.312        
##                          0.000    0.733    0.267       0.000   0.018
##                          0.000    0.030    0.014       0.000        
##                          0.000    0.013    0.005       0.000        
## --------------------------------------------------------------------
## Missouri                    10       12       15           2      39
##                            6.8     17.1     13.5         1.7        
##                          1.533    1.499    0.176       0.051        
##                          0.256    0.308    0.385       0.051   0.023
##                          0.034    0.016    0.026       0.027        
##                          0.006    0.007    0.009       0.001        
## --------------------------------------------------------------------
## Montana                      7       13        7           2      29
##                            5.0     12.7     10.0         1.3        
##                          0.763    0.008    0.905       0.422        
##                          0.241    0.448    0.241       0.069   0.017
##                          0.024    0.018    0.012       0.027        
##                          0.004    0.008    0.004       0.001        
## --------------------------------------------------------------------
## Nebraska                     3       21        7           0      31
##                            5.4     13.6     10.7         1.4        
##                          1.057    4.085    1.279       1.356        
##                          0.097    0.677    0.226       0.000   0.018
##                          0.010    0.028    0.012       0.000        
##                          0.002    0.012    0.004       0.000        
## --------------------------------------------------------------------
## Nevada                       3       19        9           1      32
##                            5.6     14.0     11.0         1.4        
##                          1.179    1.790    0.379       0.114        
##                          0.094    0.594    0.281       0.031   0.019
##                          0.010    0.026    0.015       0.014        
##                          0.002    0.011    0.005       0.001        
## --------------------------------------------------------------------
## New Hampshire               13        9       10           1      33
##                            5.7     14.4     11.4         1.4        
##                          9.207    2.045    0.170       0.136        
##                          0.394    0.273    0.303       0.030   0.020
##                          0.044    0.012    0.017       0.014        
##                          0.008    0.005    0.006       0.001        
## --------------------------------------------------------------------
## New Jersey                   7       13       12           6      38
##                            6.6     16.6     13.1         1.7        
##                          0.024    0.788    0.095      11.323        
##                          0.184    0.342    0.316       0.158   0.022
##                          0.024    0.018    0.021       0.081        
##                          0.004    0.008    0.007       0.004        
## --------------------------------------------------------------------
## New Mexico                   0       23        7           0      30
##                            5.2     13.1     10.4         1.3        
##                          5.213    7.439    1.087       1.312        
##                          0.000    0.767    0.233       0.000   0.018
##                          0.000    0.031    0.012       0.000        
##                          0.000    0.014    0.004       0.000        
## --------------------------------------------------------------------
## New York                     5       16       11           1      33
##                            5.7     14.4     11.4         1.4        
##                          0.094    0.170    0.013       0.136        
##                          0.152    0.485    0.333       0.030   0.020
##                          0.017    0.022    0.019       0.014        
##                          0.003    0.009    0.007       0.001        
## --------------------------------------------------------------------
## North Carolina               9       12       17           1      39
##                            6.8     17.1     13.5         1.7        
##                          0.729    1.499    0.930       0.292        
##                          0.231    0.308    0.436       0.026   0.023
##                          0.031    0.016    0.029       0.014        
##                          0.005    0.007    0.010       0.001        
## --------------------------------------------------------------------
## North Dakota                 8       11       12           0      31
##                            5.4     13.6     10.7         1.4        
##                          1.268    0.483    0.158       1.356        
##                          0.258    0.355    0.387       0.000   0.018
##                          0.027    0.015    0.021       0.000        
##                          0.005    0.007    0.007       0.000        
## --------------------------------------------------------------------
## Ohio                         5       15       10           1      31
##                            5.4     13.6     10.7         1.4        
##                          0.028    0.153    0.046       0.093        
##                          0.161    0.484    0.323       0.032   0.018
##                          0.017    0.020    0.017       0.014        
##                          0.003    0.009    0.006       0.001        
## --------------------------------------------------------------------
## Oklahoma                     2       20       10           1      33
##                            5.7     14.4     11.4         1.4        
##                          2.432    2.148    0.170       0.136        
##                          0.061    0.606    0.303       0.030   0.020
##                          0.007    0.027    0.017       0.014        
##                          0.001    0.012    0.006       0.001        
## --------------------------------------------------------------------
## Oregon                      12        2       18           2      34
##                            5.9     14.9     11.7         1.5        
##                          6.282   11.139    3.344       0.177        
##                          0.353    0.059    0.529       0.059   0.020
##                          0.041    0.003    0.031       0.027        
##                          0.007    0.001    0.011       0.001        
## --------------------------------------------------------------------
## Pennsylvania                 9       14       11           2      36
##                            6.3     15.7     12.4         1.6        
##                          1.204    0.193    0.164       0.115        
##                          0.250    0.389    0.306       0.056   0.021
##                          0.031    0.019    0.019       0.027        
##                          0.005    0.008    0.007       0.001        
## --------------------------------------------------------------------
## Rhode Island                16        6        9           2      33
##                            5.7     14.4     11.4         1.4        
##                         18.380    4.927    0.502       0.215        
##                          0.485    0.182    0.273       0.061   0.020
##                          0.054    0.008    0.015       0.027        
##                          0.009    0.004    0.005       0.001        
## --------------------------------------------------------------------
## South Carolina               3       17       17           1      38
##                            6.6     16.6     13.1         1.7        
##                          1.966    0.009    1.150       0.264        
##                          0.079    0.447    0.447       0.026   0.022
##                          0.010    0.023    0.029       0.014        
##                          0.002    0.010    0.010       0.001        
## --------------------------------------------------------------------
## South Dakota                 1       23        7           0      31
##                            5.4     13.6     10.7         1.4        
##                          3.572    6.576    1.279       1.356        
##                          0.032    0.742    0.226       0.000   0.018
##                          0.003    0.031    0.012       0.000        
##                          0.001    0.014    0.004       0.000        
## --------------------------------------------------------------------
## Tennessee                    2       20       10           1      33
##                            5.7     14.4     11.4         1.4        
##                          2.432    2.148    0.170       0.136        
##                          0.061    0.606    0.303       0.030   0.020
##                          0.007    0.027    0.017       0.014        
##                          0.001    0.012    0.006       0.001        
## --------------------------------------------------------------------
## Texas                        1       21        8           0      30
##                            5.2     13.1     10.4         1.3        
##                          3.405    4.732    0.535       1.312        
##                          0.033    0.700    0.267       0.000   0.018
##                          0.003    0.028    0.014       0.000        
##                          0.001    0.012    0.005       0.000        
## --------------------------------------------------------------------
## Utah                         3       17       14           2      36
##                            6.3     15.7     12.4         1.6        
##                          1.694    0.100    0.200       0.115        
##                          0.083    0.472    0.389       0.056   0.021
##                          0.010    0.023    0.024       0.027        
##                          0.002    0.010    0.008       0.001        
## --------------------------------------------------------------------
## Vermont                     10        7        9           4      30
##                            5.2     13.1     10.4         1.3        
##                          4.396    2.855    0.177       5.507        
##                          0.333    0.233    0.300       0.133   0.018
##                          0.034    0.009    0.015       0.054        
##                          0.006    0.004    0.005       0.002        
## --------------------------------------------------------------------
## Virginia                     8       15        8           1      32
##                            5.6     14.0     11.0         1.4        
##                          1.070    0.072    0.839       0.114        
##                          0.250    0.469    0.250       0.031   0.019
##                          0.027    0.020    0.014       0.014        
##                          0.005    0.009    0.005       0.001        
## --------------------------------------------------------------------
## Washington                   3       19        9           1      32
##                            5.6     14.0     11.0         1.4        
##                          1.179    1.790    0.379       0.114        
##                          0.094    0.594    0.281       0.031   0.019
##                          0.010    0.026    0.015       0.014        
##                          0.002    0.011    0.005       0.001        
## --------------------------------------------------------------------
## West Virginia                5       12       15           2      34
##                            5.9     14.9     11.7         1.5        
##                          0.139    0.554    0.908       0.177        
##                          0.147    0.353    0.441       0.059   0.020
##                          0.017    0.016    0.026       0.027        
##                          0.003    0.007    0.009       0.001        
## --------------------------------------------------------------------
## Wisconsin                    9        5       24           1      39
##                            6.8     17.1     13.5         1.7        
##                          0.729    8.522    8.251       0.292        
##                          0.231    0.128    0.615       0.026   0.023
##                          0.031    0.007    0.041       0.014        
##                          0.005    0.003    0.014       0.001        
## --------------------------------------------------------------------
## Wyoming                      2       13       14           0      29
##                            5.0     12.7     10.0         1.3        
##                          1.833    0.008    1.591       1.268        
##                          0.069    0.448    0.483       0.000   0.017
##                          0.007    0.018    0.024       0.000        
##                          0.001    0.008    0.008       0.000        
## --------------------------------------------------------------------
## Total                      294      740      584          74    1692
##                          0.174    0.437    0.345       0.044        
## ====================================================================
## ====================================================================== 
## 
## CrossTab of State_Full2 by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## =======================================================================
##                            crs$dataset[[crs$target]]
## crs$dataset[[i]]             High      Low   Medium   Very High   Total
## -----------------------------------------------------------------------
## AK-Alaska                       2       14       14           2      32
##                               5.6     14.0     11.0         1.4        
##                             2.280    0.000    0.791       0.258        
##                             0.062    0.438    0.438       0.062   0.019
##                             0.007    0.019    0.024       0.027        
##                             0.001    0.008    0.008       0.001        
## -----------------------------------------------------------------------
## AL-Alabama                      6       17        9           4      36
##                               6.3     15.7     12.4         1.6        
##                             0.010    0.100    0.944       3.737        
##                             0.167    0.472    0.250       0.111   0.021
##                             0.020    0.023    0.015       0.054        
##                             0.004    0.010    0.005       0.002        
## -----------------------------------------------------------------------
## AR-Arkansas                     4       13       19           1      37
##                               6.4     16.2     12.8         1.6        
##                             0.918    0.626    3.039       0.236        
##                             0.108    0.351    0.514       0.027   0.022
##                             0.014    0.018    0.033       0.014        
##                             0.002    0.008    0.011       0.001        
## -----------------------------------------------------------------------
## AZ-Arizona                     10       14       15           1      40
##                               7.0     17.5     13.8         1.7        
##                             1.338    0.698    0.103       0.321        
##                             0.250    0.350    0.375       0.025   0.024
##                             0.034    0.019    0.026       0.014        
##                             0.006    0.008    0.009       0.001        
## -----------------------------------------------------------------------
## CA-California                   6       18        7           0      31
##                               5.4     13.6     10.7         1.4        
##                             0.070    1.455    1.279       1.356        
##                             0.194    0.581    0.226       0.000   0.018
##                             0.020    0.024    0.012       0.000        
##                             0.004    0.011    0.004       0.000        
## -----------------------------------------------------------------------
## CO-Colorado                     4       21       12           0      37
##                               6.4     16.2     12.8         1.6        
##                             0.918    1.434    0.047       1.618        
##                             0.108    0.568    0.324       0.000   0.022
##                             0.014    0.028    0.021       0.000        
##                             0.002    0.012    0.007       0.000        
## -----------------------------------------------------------------------
## CT-Connecticut                  9       14        9           1      33
##                               5.7     14.4     11.4         1.4        
##                             1.860    0.013    0.502       0.136        
##                             0.273    0.424    0.273       0.030   0.020
##                             0.031    0.019    0.015       0.014        
##                             0.005    0.008    0.005       0.001        
## -----------------------------------------------------------------------
## DC-District of Columbia         3       15        7           0      25
##                               4.3     10.9      8.6         1.1        
##                             0.416    1.512    0.307       1.093        
##                             0.120    0.600    0.280       0.000   0.015
##                             0.010    0.020    0.012       0.000        
##                             0.002    0.009    0.004       0.000        
## -----------------------------------------------------------------------
## DE-Delaware                     3       17       10           2      32
##                               5.6     14.0     11.0         1.4        
##                             1.179    0.645    0.099       0.258        
##                             0.094    0.531    0.312       0.062   0.019
##                             0.010    0.023    0.017       0.027        
##                             0.002    0.010    0.006       0.001        
## -----------------------------------------------------------------------
## FL-Florida                      4       20        9           1      34
##                               5.9     14.9     11.7         1.5        
##                             0.616    1.770    0.638       0.159        
##                             0.118    0.588    0.265       0.029   0.020
##                             0.014    0.027    0.015       0.014        
##                             0.002    0.012    0.005       0.001        
## -----------------------------------------------------------------------
## GA-Georgia                      6       15       17           1      39
##                               6.8     17.1     13.5         1.7        
##                             0.089    0.248    0.930       0.292        
##                             0.154    0.385    0.436       0.026   0.023
##                             0.020    0.020    0.029       0.014        
##                             0.004    0.009    0.010       0.001        
## -----------------------------------------------------------------------
## HI-Hawaii                       1       19       11           0      31
##                               5.4     13.6     10.7         1.4        
##                             3.572    2.184    0.008       1.356        
##                             0.032    0.613    0.355       0.000   0.018
##                             0.003    0.026    0.019       0.000        
##                             0.001    0.011    0.007       0.000        
## -----------------------------------------------------------------------
## IA-Iowa                         2       23        6           1      32
##                               5.6     14.0     11.0         1.4        
##                             2.280    5.794    2.304       0.114        
##                             0.062    0.719    0.188       0.031   0.019
##                             0.007    0.031    0.010       0.014        
##                             0.001    0.014    0.004       0.001        
## -----------------------------------------------------------------------
## ID-Idaho                        5        8       14           5      32
##                               5.6     14.0     11.0         1.4        
##                             0.056    2.568    0.791       9.263        
##                             0.156    0.250    0.438       0.156   0.019
##                             0.017    0.011    0.024       0.068        
##                             0.003    0.005    0.008       0.003        
## -----------------------------------------------------------------------
## IL-Illinois                     2       16       12           2      32
##                               5.6     14.0     11.0         1.4        
##                             2.280    0.287    0.083       0.258        
##                             0.062    0.500    0.375       0.062   0.019
##                             0.007    0.022    0.021       0.027        
##                             0.001    0.009    0.007       0.001        
## -----------------------------------------------------------------------
## IN-Indiana                      9        9       13           2      33
##                               5.7     14.4     11.4         1.4        
##                             1.860    2.045    0.228       0.215        
##                             0.273    0.273    0.394       0.061   0.020
##                             0.031    0.012    0.022       0.027        
##                             0.005    0.005    0.008       0.001        
## -----------------------------------------------------------------------
## KS-Kansas                       1       14       15           0      30
##                               5.2     13.1     10.4         1.3        
##                             3.405    0.059    2.084       1.312        
##                             0.033    0.467    0.500       0.000   0.018
##                             0.003    0.019    0.026       0.000        
##                             0.001    0.008    0.009       0.000        
## -----------------------------------------------------------------------
## KY-Kentucky                     2       17       11           2      32
##                               5.6     14.0     11.0         1.4        
##                             2.280    0.645    0.000       0.258        
##                             0.062    0.531    0.344       0.062   0.019
##                             0.007    0.023    0.019       0.027        
##                             0.001    0.010    0.007       0.001        
## -----------------------------------------------------------------------
## LA-Louisiana                    1       24        6           1      32
##                               5.6     14.0     11.0         1.4        
##                             3.740    7.152    2.304       0.114        
##                             0.031    0.750    0.188       0.031   0.019
##                             0.003    0.032    0.010       0.014        
##                             0.001    0.014    0.004       0.001        
## -----------------------------------------------------------------------
## MA-Massachusetts                9       15        7           2      33
##                               5.7     14.4     11.4         1.4        
##                             1.860    0.022    1.692       0.215        
##                             0.273    0.455    0.212       0.061   0.020
##                             0.031    0.020    0.012       0.027        
##                             0.005    0.009    0.004       0.001        
## -----------------------------------------------------------------------
## MD-Maryland                    10        9       19           2      40
##                               7.0     17.5     13.8         1.7        
##                             1.338    4.124    1.954       0.036        
##                             0.250    0.225    0.475       0.050   0.024
##                             0.034    0.012    0.033       0.027        
##                             0.006    0.005    0.011       0.001        
## -----------------------------------------------------------------------
## ME-Maine                       12        4        6           5      27
##                               4.7     11.8      9.3         1.2        
##                            11.385    5.163    1.182      12.352        
##                             0.444    0.148    0.222       0.185   0.016
##                             0.041    0.005    0.010       0.068        
##                             0.007    0.002    0.004       0.003        
## -----------------------------------------------------------------------
## MI-Michigan                     6        5       20           1      32
##                               5.6     14.0     11.0         1.4        
##                             0.035    5.782    7.261       0.114        
##                             0.188    0.156    0.625       0.031   0.019
##                             0.020    0.007    0.034       0.014        
##                             0.004    0.003    0.012       0.001        
## -----------------------------------------------------------------------
## MN-Minnesota                   21        2        8           3      34
##                               5.9     14.9     11.7         1.5        
##                            38.555   11.139    1.189       1.539        
##                             0.618    0.059    0.235       0.088   0.020
##                             0.071    0.003    0.014       0.041        
##                             0.012    0.001    0.005       0.002        
## -----------------------------------------------------------------------
## MO-Missouri                    10       12       15           2      39
##                               6.8     17.1     13.5         1.7        
##                             1.533    1.499    0.176       0.051        
##                             0.256    0.308    0.385       0.051   0.023
##                             0.034    0.016    0.026       0.027        
##                             0.006    0.007    0.009       0.001        
## -----------------------------------------------------------------------
## MS-Mississippi                  0       22        8           0      30
##                               5.2     13.1     10.4         1.3        
##                             5.213    6.009    0.535       1.312        
##                             0.000    0.733    0.267       0.000   0.018
##                             0.000    0.030    0.014       0.000        
##                             0.000    0.013    0.005       0.000        
## -----------------------------------------------------------------------
## MT-Montana                      7       13        7           2      29
##                               5.0     12.7     10.0         1.3        
##                             0.763    0.008    0.905       0.422        
##                             0.241    0.448    0.241       0.069   0.017
##                             0.024    0.018    0.012       0.027        
##                             0.004    0.008    0.004       0.001        
## -----------------------------------------------------------------------
## NC-North Carolina               9       12       17           1      39
##                               6.8     17.1     13.5         1.7        
##                             0.729    1.499    0.930       0.292        
##                             0.231    0.308    0.436       0.026   0.023
##                             0.031    0.016    0.029       0.014        
##                             0.005    0.007    0.010       0.001        
## -----------------------------------------------------------------------
## ND-North Dakota                 8       11       12           0      31
##                               5.4     13.6     10.7         1.4        
##                             1.268    0.483    0.158       1.356        
##                             0.258    0.355    0.387       0.000   0.018
##                             0.027    0.015    0.021       0.000        
##                             0.005    0.007    0.007       0.000        
## -----------------------------------------------------------------------
## NE-Nebraska                     3       21        7           0      31
##                               5.4     13.6     10.7         1.4        
##                             1.057    4.085    1.279       1.356        
##                             0.097    0.677    0.226       0.000   0.018
##                             0.010    0.028    0.012       0.000        
##                             0.002    0.012    0.004       0.000        
## -----------------------------------------------------------------------
## NH-New Hampshire               13        9       10           1      33
##                               5.7     14.4     11.4         1.4        
##                             9.207    2.045    0.170       0.136        
##                             0.394    0.273    0.303       0.030   0.020
##                             0.044    0.012    0.017       0.014        
##                             0.008    0.005    0.006       0.001        
## -----------------------------------------------------------------------
## NJ-New Jersey                   7       13       12           6      38
##                               6.6     16.6     13.1         1.7        
##                             0.024    0.788    0.095      11.323        
##                             0.184    0.342    0.316       0.158   0.022
##                             0.024    0.018    0.021       0.081        
##                             0.004    0.008    0.007       0.004        
## -----------------------------------------------------------------------
## NM-New Mexico                   0       23        7           0      30
##                               5.2     13.1     10.4         1.3        
##                             5.213    7.439    1.087       1.312        
##                             0.000    0.767    0.233       0.000   0.018
##                             0.000    0.031    0.012       0.000        
##                             0.000    0.014    0.004       0.000        
## -----------------------------------------------------------------------
## NV-Nevada                       3       19        9           1      32
##                               5.6     14.0     11.0         1.4        
##                             1.179    1.790    0.379       0.114        
##                             0.094    0.594    0.281       0.031   0.019
##                             0.010    0.026    0.015       0.014        
##                             0.002    0.011    0.005       0.001        
## -----------------------------------------------------------------------
## NY-New York                     5       16       11           1      33
##                               5.7     14.4     11.4         1.4        
##                             0.094    0.170    0.013       0.136        
##                             0.152    0.485    0.333       0.030   0.020
##                             0.017    0.022    0.019       0.014        
##                             0.003    0.009    0.007       0.001        
## -----------------------------------------------------------------------
## OH-Ohio                         5       15       10           1      31
##                               5.4     13.6     10.7         1.4        
##                             0.028    0.153    0.046       0.093        
##                             0.161    0.484    0.323       0.032   0.018
##                             0.017    0.020    0.017       0.014        
##                             0.003    0.009    0.006       0.001        
## -----------------------------------------------------------------------
## OK-Oklahoma                     2       20       10           1      33
##                               5.7     14.4     11.4         1.4        
##                             2.432    2.148    0.170       0.136        
##                             0.061    0.606    0.303       0.030   0.020
##                             0.007    0.027    0.017       0.014        
##                             0.001    0.012    0.006       0.001        
## -----------------------------------------------------------------------
## OR-Oregon                      12        2       18           2      34
##                               5.9     14.9     11.7         1.5        
##                             6.282   11.139    3.344       0.177        
##                             0.353    0.059    0.529       0.059   0.020
##                             0.041    0.003    0.031       0.027        
##                             0.007    0.001    0.011       0.001        
## -----------------------------------------------------------------------
## PA-Pennsylvania                 9       14       11           2      36
##                               6.3     15.7     12.4         1.6        
##                             1.204    0.193    0.164       0.115        
##                             0.250    0.389    0.306       0.056   0.021
##                             0.031    0.019    0.019       0.027        
##                             0.005    0.008    0.007       0.001        
## -----------------------------------------------------------------------
## RI-Rhode Island                16        6        9           2      33
##                               5.7     14.4     11.4         1.4        
##                            18.380    4.927    0.502       0.215        
##                             0.485    0.182    0.273       0.061   0.020
##                             0.054    0.008    0.015       0.027        
##                             0.009    0.004    0.005       0.001        
## -----------------------------------------------------------------------
## SC-South Carolina               3       17       17           1      38
##                               6.6     16.6     13.1         1.7        
##                             1.966    0.009    1.150       0.264        
##                             0.079    0.447    0.447       0.026   0.022
##                             0.010    0.023    0.029       0.014        
##                             0.002    0.010    0.010       0.001        
## -----------------------------------------------------------------------
## SD-South Dakota                 1       23        7           0      31
##                               5.4     13.6     10.7         1.4        
##                             3.572    6.576    1.279       1.356        
##                             0.032    0.742    0.226       0.000   0.018
##                             0.003    0.031    0.012       0.000        
##                             0.001    0.014    0.004       0.000        
## -----------------------------------------------------------------------
## TN-Tennessee                    2       20       10           1      33
##                               5.7     14.4     11.4         1.4        
##                             2.432    2.148    0.170       0.136        
##                             0.061    0.606    0.303       0.030   0.020
##                             0.007    0.027    0.017       0.014        
##                             0.001    0.012    0.006       0.001        
## -----------------------------------------------------------------------
## TX-Texas                        1       21        8           0      30
##                               5.2     13.1     10.4         1.3        
##                             3.405    4.732    0.535       1.312        
##                             0.033    0.700    0.267       0.000   0.018
##                             0.003    0.028    0.014       0.000        
##                             0.001    0.012    0.005       0.000        
## -----------------------------------------------------------------------
## UT-Utah                         3       17       14           2      36
##                               6.3     15.7     12.4         1.6        
##                             1.694    0.100    0.200       0.115        
##                             0.083    0.472    0.389       0.056   0.021
##                             0.010    0.023    0.024       0.027        
##                             0.002    0.010    0.008       0.001        
## -----------------------------------------------------------------------
## VA-Virginia                     8       15        8           1      32
##                               5.6     14.0     11.0         1.4        
##                             1.070    0.072    0.839       0.114        
##                             0.250    0.469    0.250       0.031   0.019
##                             0.027    0.020    0.014       0.014        
##                             0.005    0.009    0.005       0.001        
## -----------------------------------------------------------------------
## VT-Vermont                     10        7        9           4      30
##                               5.2     13.1     10.4         1.3        
##                             4.396    2.855    0.177       5.507        
##                             0.333    0.233    0.300       0.133   0.018
##                             0.034    0.009    0.015       0.054        
##                             0.006    0.004    0.005       0.002        
## -----------------------------------------------------------------------
## WA-Washington                   3       19        9           1      32
##                               5.6     14.0     11.0         1.4        
##                             1.179    1.790    0.379       0.114        
##                             0.094    0.594    0.281       0.031   0.019
##                             0.010    0.026    0.015       0.014        
##                             0.002    0.011    0.005       0.001        
## -----------------------------------------------------------------------
## WI-Wisconsin                    9        5       24           1      39
##                               6.8     17.1     13.5         1.7        
##                             0.729    8.522    8.251       0.292        
##                             0.231    0.128    0.615       0.026   0.023
##                             0.031    0.007    0.041       0.014        
##                             0.005    0.003    0.014       0.001        
## -----------------------------------------------------------------------
## WV-West Virginia                5       12       15           2      34
##                               5.9     14.9     11.7         1.5        
##                             0.139    0.554    0.908       0.177        
##                             0.147    0.353    0.441       0.059   0.020
##                             0.017    0.016    0.026       0.027        
##                             0.003    0.007    0.009       0.001        
## -----------------------------------------------------------------------
## WY-Wyoming                      2       13       14           0      29
##                               5.0     12.7     10.0         1.3        
##                             1.833    0.008    1.591       1.268        
##                             0.069    0.448    0.483       0.000   0.017
##                             0.007    0.018    0.024       0.000        
##                             0.001    0.008    0.008       0.000        
## -----------------------------------------------------------------------
## Total                         294      740      584          74    1692
##                             0.174    0.437    0.345       0.044        
## =======================================================================
## ====================================================================== 
## 
## CrossTab of State_Region by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ====================================================================
##                          crs$dataset[[crs$target]]
## crs$dataset[[i]]           High     Low   Medium   Very High   Total
## --------------------------------------------------------------------
## D1 New England               69      55       50          15     189
##                            32.8    82.7     65.2         8.3        
##                          39.814   9.255    3.558       5.486        
##                           0.365   0.291    0.265       0.079   0.112
##                           0.235   0.074    0.086       0.203        
##                           0.041   0.033    0.030       0.009        
## --------------------------------------------------------------------
## D2 Middle Atlantic           21      43       34           9     107
##                            18.6    46.8     36.9         4.7        
##                           0.312   0.308    0.233       3.989        
##                           0.196   0.402    0.318       0.084   0.063
##                           0.071   0.058    0.058       0.122        
##                           0.012   0.025    0.020       0.005        
## --------------------------------------------------------------------
## D3 East North Central        31      50       79           7     167
##                            29.0    73.0     57.6         7.3        
##                           0.135   7.267    7.915       0.013        
##                           0.186   0.299    0.473       0.042   0.099
##                           0.105   0.068    0.135       0.095        
##                           0.018   0.030    0.047       0.004        
## --------------------------------------------------------------------
## D4 West North Central        46     106       70           6     228
##                            39.6    99.7     78.7        10.0        
##                           1.028   0.396    0.961       1.582        
##                           0.202   0.465    0.307       0.026   0.135
##                           0.156   0.143    0.120       0.081        
##                           0.027   0.063    0.041       0.004        
## --------------------------------------------------------------------
## D5 South Atlantic            51     132      119          11     313
##                            54.4   136.9    108.0        13.7        
##                           0.211   0.175    1.113       0.528        
##                           0.163   0.422    0.380       0.035   0.185
##                           0.173   0.178    0.204       0.149        
##                           0.030   0.078    0.070       0.007        
## --------------------------------------------------------------------
## D6 East South Central        10      76       38           7     131
##                            22.8    57.3     45.2         5.7        
##                           7.156   6.108    1.151       0.282        
##                           0.076   0.580    0.290       0.053   0.077
##                           0.034   0.103    0.065       0.095        
##                           0.006   0.045    0.022       0.004        
## --------------------------------------------------------------------
## D7 West South Central         8      78       43           3     132
##                            22.9    57.7     45.6         5.8        
##                           9.727   7.117    0.144       1.332        
##                           0.061   0.591    0.326       0.023   0.078
##                           0.027   0.105    0.074       0.041        
##                           0.005   0.046    0.025       0.002        
## --------------------------------------------------------------------
## D8 Mountain                  34     128       92          11     265
##                            46.0   115.9     91.5        11.6        
##                           3.151   1.264    0.003       0.030        
##                           0.128   0.483    0.347       0.042   0.157
##                           0.116   0.173    0.158       0.149        
##                           0.020   0.076    0.054       0.007        
## --------------------------------------------------------------------
## D9 Pacific                   24      72       59           5     160
##                            27.8    70.0     55.2         7.0        
##                           0.520   0.059    0.258       0.570        
##                           0.150   0.450    0.369       0.031   0.095
##                           0.082   0.097    0.101       0.068        
##                           0.014   0.043    0.035       0.003        
## --------------------------------------------------------------------
## Total                       294     740      584          74    1692
##                           0.174   0.437    0.345       0.044        
## ====================================================================
## ====================================================================== 
## 
## CrossTab of Source_UC by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ================================================================
##                     crs$dataset[[crs$target]]
## crs$dataset[[i]]      High      Low   Medium   Very High   Total
## ----------------------------------------------------------------
## ADDM                    38        5       36           7      86
##                       14.9     37.6     29.7         3.8        
##                     35.575   28.277    1.344       2.789        
##                      0.442    0.058    0.419       0.081   0.051
##                      0.129    0.007    0.062       0.095        
##                      0.022    0.003    0.021       0.004        
## ----------------------------------------------------------------
## MEDI                    74      344      225          12     655
##                      113.8    286.5    226.1        28.6        
##                     13.926   11.555    0.005       9.673        
##                      0.113    0.525    0.344       0.018   0.387
##                      0.252    0.465    0.385       0.162        
##                      0.044    0.203    0.133       0.007        
## ----------------------------------------------------------------
## NSCH                    38        0        5          55      98
##                       17.0     42.9     33.8         4.3        
##                     25.828   42.861   24.564     600.064        
##                      0.388    0.000    0.051       0.561   0.058
##                      0.129    0.000    0.009       0.743        
##                      0.022    0.000    0.003       0.033        
## ----------------------------------------------------------------
## SPED                   144      391      318           0     853
##                      148.2    373.1    294.4        37.3        
##                      0.120    0.863    1.889      37.306        
##                      0.169    0.458    0.373       0.000   0.504
##                      0.490    0.528    0.545       0.000        
##                      0.085    0.231    0.188       0.000        
## ----------------------------------------------------------------
## Total                  294      740      584          74    1692
##                      0.174    0.437    0.345       0.044        
## ================================================================
## ====================================================================== 
## 
## CrossTab of Source_Full3 by target variable Prevalence_Risk4
## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##    Cell Contents 
## |-------------------------|
## |                       N | 
## |              Expected N | 
## | Chi-square contribution | 
## |           N / Row Total | 
## |           N / Col Total | 
## |         N / Table Total | 
## |-------------------------|
## 
## ================================================================================
##                                crs$dataset[[crs$target]]
## crs$dataset[[i]]                  High       Low    Medium   Very High     Total
## --------------------------------------------------------------------------------
## ADDM Atsm & Dvlpmntl Ds M N         38         5        36           7        86
##                                   14.9      37.6      29.7         3.8          
##                                 35.575    28.277     1.344       2.789          
##                                  0.442     0.058     0.419       0.081     0.051
##                                  0.129     0.007     0.062       0.095          
##                                  0.022     0.003     0.021       0.004          
## --------------------------------------------------------------------------------
## MEDI Medicaid                       74       344       225          12       655
##                                  113.8     286.5     226.1        28.6          
##                                 13.926    11.555     0.005       9.673          
##                                  0.113     0.525     0.344       0.018     0.387
##                                  0.252     0.465     0.385       0.162          
##                                  0.044     0.203     0.133       0.007          
## --------------------------------------------------------------------------------
## NSCH Ntnl Srvy of Chldrn' H         38         0         5          55        98
##                                   17.0      42.9      33.8         4.3          
##                                 25.828    42.861    24.564     600.064          
##                                  0.388     0.000     0.051       0.561     0.058
##                                  0.129     0.000     0.009       0.743          
##                                  0.022     0.000     0.003       0.033          
## --------------------------------------------------------------------------------
## SPED Special Edctn Chld Cnt        144       391       318           0       853
##                                  148.2     373.1     294.4        37.3          
##                                  0.120     0.863     1.889      37.306          
##                                  0.169     0.458     0.373       0.000     0.504
##                                  0.490     0.528     0.545       0.000          
##                                  0.085     0.231     0.188       0.000          
## --------------------------------------------------------------------------------
## Total                              294       740       584          74      1692
##                                  0.174     0.437     0.345       0.044          
## ================================================================================
## ======================================================================
<h3>
Rattle: EDA Explore & Test: Distribution
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 10:45:21 x86_64-pc-linux-gnu 

# Display box plots for the selected variables. 

# Use ggplot2 to generate box plot for Denominator

# Generate a box plot.

p01 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  ggplot2::ggplot(ggplot2::aes(y=Denominator)) +
  ggplot2::geom_boxplot(ggplot2::aes(x="All"), notch=TRUE, fill="grey") +
  ggplot2::stat_summary(ggplot2::aes(x="All"), fun.y=mean, geom="point", shape=8) +
  ggplot2::geom_boxplot(ggplot2::aes(x=Prevalence_Risk4, fill=Prevalence_Risk4), notch=TRUE) +
  ggplot2::stat_summary(ggplot2::aes(x=Prevalence_Risk4), fun.y=mean, geom="point", shape=8) +
  ggplot2::xlab("Prevalence_Risk4\n\nRattle 2019-Dec-23 10:45:21 iss-user") +
  ggplot2::ggtitle("Distribution of Denominator (sample)\nby Prevalence_Risk4") +
  ggplot2::theme(legend.position="none")

# Use ggplot2 to generate box plot for Prevalence

# Generate a box plot.

p02 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  ggplot2::ggplot(ggplot2::aes(y=Prevalence)) +
  ggplot2::geom_boxplot(ggplot2::aes(x="All"), notch=TRUE, fill="grey") +
  ggplot2::stat_summary(ggplot2::aes(x="All"), fun.y=mean, geom="point", shape=8) +
  ggplot2::geom_boxplot(ggplot2::aes(x=Prevalence_Risk4, fill=Prevalence_Risk4), notch=TRUE) +
  ggplot2::stat_summary(ggplot2::aes(x=Prevalence_Risk4), fun.y=mean, geom="point", shape=8) +
  ggplot2::xlab("Prevalence_Risk4\n\nRattle 2019-Dec-23 10:45:21 iss-user") +
  ggplot2::ggtitle("Distribution of Prevalence (sample)\nby Prevalence_Risk4") +
  ggplot2::theme(legend.position="none")

# Use ggplot2 to generate box plot for Lower.CI

# Generate a box plot.

p03 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  ggplot2::ggplot(ggplot2::aes(y=Lower.CI)) +
  ggplot2::geom_boxplot(ggplot2::aes(x="All"), notch=TRUE, fill="grey") +
  ggplot2::stat_summary(ggplot2::aes(x="All"), fun.y=mean, geom="point", shape=8) +
  ggplot2::geom_boxplot(ggplot2::aes(x=Prevalence_Risk4, fill=Prevalence_Risk4), notch=TRUE) +
  ggplot2::stat_summary(ggplot2::aes(x=Prevalence_Risk4), fun.y=mean, geom="point", shape=8) +
  ggplot2::xlab("Prevalence_Risk4\n\nRattle 2019-Dec-23 10:45:21 iss-user") +
  ggplot2::ggtitle("Distribution of Lower.CI (sample)\nby Prevalence_Risk4") +
  ggplot2::theme(legend.position="none")

# Use ggplot2 to generate box plot for Upper.CI

# Generate a box plot.

p04 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  ggplot2::ggplot(ggplot2::aes(y=Upper.CI)) +
  ggplot2::geom_boxplot(ggplot2::aes(x="All"), notch=TRUE, fill="grey") +
  ggplot2::stat_summary(ggplot2::aes(x="All"), fun.y=mean, geom="point", shape=8) +
  ggplot2::geom_boxplot(ggplot2::aes(x=Prevalence_Risk4, fill=Prevalence_Risk4), notch=TRUE) +
  ggplot2::stat_summary(ggplot2::aes(x=Prevalence_Risk4), fun.y=mean, geom="point", shape=8) +
  ggplot2::xlab("Prevalence_Risk4\n\nRattle 2019-Dec-23 10:45:22 iss-user") +
  ggplot2::ggtitle("Distribution of Upper.CI (sample)\nby Prevalence_Risk4") +
  ggplot2::theme(legend.position="none")

# Display the plots.

gridExtra::grid.arrange(p01, p02, p03, p04)
## notch went outside hinges. Try setting notch=FALSE.


#=======================================================================
# Rattle timestamp: 2019-12-23 10:43:09 x86_64-pc-linux-gnu 

# Display histogram plots for the selected variables. 

# Use ggplot2 to generate histogram plot for Denominator

# Generate the plot.

p01 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Denominator, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Denominator)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Denominator\n\nRattle 2019-Dec-23 10:43:09 iss-user") +
  ggplot2::ggtitle("Distribution of Denominator (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Use ggplot2 to generate histogram plot for Prevalence

# Generate the plot.

p02 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Prevalence, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Prevalence)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Prevalence\n\nRattle 2019-Dec-23 10:43:09 iss-user") +
  ggplot2::ggtitle("Distribution of Prevalence (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Use ggplot2 to generate histogram plot for Lower.CI

# Generate the plot.

p03 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Lower.CI, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Lower.CI)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Lower.CI\n\nRattle 2019-Dec-23 10:43:09 iss-user") +
  ggplot2::ggtitle("Distribution of Lower.CI (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Use ggplot2 to generate histogram plot for Upper.CI

# Generate the plot.

p04 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Upper.CI, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Upper.CI)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Upper.CI\n\nRattle 2019-Dec-23 10:43:09 iss-user") +
  ggplot2::ggtitle("Distribution of Upper.CI (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Display the plots.

gridExtra::grid.arrange(p01, p02, p03, p04)


#=======================================================================
# Rattle timestamp: 2019-12-23 10:48:49 x86_64-pc-linux-gnu 

# Display histogram plots for the selected variables. 

# Use ggplot2 to generate histogram plot for Year

# Generate the plot.

p01 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Year, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Year)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Year\n\nRattle 2019-Dec-23 10:48:49 iss-user") +
  ggplot2::ggtitle("Distribution of Year (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Display the plots.

gridExtra::grid.arrange(p01)


if(!require(GGally)){install.packages("GGally")}
## Loading required package: GGally
## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2
library('GGally')

#=======================================================================
# Rattle timestamp: 2019-12-23 10:54:13 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(2,3,4,5),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'


#=======================================================================
# Rattle timestamp: 2019-12-23 11:06:10 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(3,11,13),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'


#=======================================================================
# Rattle timestamp: 2019-12-23 11:07:28 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(3,16,19),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning: Removed 1125 rows containing missing values (geom_point).
## Warning: Removed 1125 rows containing non-finite values (stat_density).
## Warning: Groups with fewer than two data points have been dropped.
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning: Removed 1125 rows containing missing values (geom_point).

## Warning: Removed 1125 rows containing missing values (geom_point).
## Warning: Removed 1125 rows containing non-finite values (stat_density).
## Warning: Groups with fewer than two data points have been dropped.


#=======================================================================
# Rattle timestamp: 2019-12-23 11:11:18 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(3,22,25,28,31),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1129 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1133 rows containing missing values
## Warning: Removed 1125 rows containing missing values (geom_point).
## Warning: Removed 1125 rows containing non-finite values (stat_density).
## Warning: Groups with fewer than two data points have been dropped.
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1125 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1129 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1133 rows containing missing values
## Warning: Removed 1125 rows containing missing values (geom_point).

## Warning: Removed 1125 rows containing missing values (geom_point).
## Warning: Removed 1125 rows containing non-finite values (stat_density).
## Warning: Groups with fewer than two data points have been dropped.
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1129 rows containing missing values
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1133 rows containing missing values
## Warning: Removed 1129 rows containing missing values (geom_point).

## Warning: Removed 1129 rows containing missing values (geom_point).

## Warning: Removed 1129 rows containing missing values (geom_point).
## Warning: Removed 1129 rows containing non-finite values (stat_density).
## Warning in (function (data, mapping, alignPercent = 0.6, method = "pearson", :
## Removed 1133 rows containing missing values
## Warning: Removed 1133 rows containing missing values (geom_point).

## Warning: Removed 1133 rows containing missing values (geom_point).

## Warning: Removed 1133 rows containing missing values (geom_point).

## Warning: Removed 1133 rows containing missing values (geom_point).
## Warning: Removed 1133 rows containing non-finite values (stat_density).


#=======================================================================
# Rattle timestamp: 2019-12-23 11:15:09 x86_64-pc-linux-gnu 

# Mosaic Plot 

# Generate the table data for plotting.

ds <- table(crs$dataset[crs$train,]$State, crs$dataset[crs$train,]$Prevalence_Risk4)

# Sort the entries.

ord <- order(apply(ds, 1, sum), decreasing=TRUE)

# Plot the data.

mosaicplot(ds[ord,], main="Mosaic of State (sample)
by Prevalence_Risk4", sub="Rattle 2019-Dec-23 11:15:09 iss-user", color=colorspace::rainbow_hcl(5)[-1], cex=0.7, xlab="State", ylab="Prevalence_Risk4")


#=======================================================================
# Rattle timestamp: 2019-12-23 14:50:59 x86_64-pc-linux-gnu 

# Mosaic Plot 

# Generate the table data for plotting.

ds <- table(crs$dataset[crs$train,]$State_Region, crs$dataset[crs$train,]$Prevalence_Risk4)

# Sort the entries.

ord <- order(apply(ds, 1, sum), decreasing=TRUE)

# Plot the data.

mosaicplot(ds[ord,], main="Mosaic of State_Region (sample)
by Prevalence_Risk4", sub="Rattle 2019-Dec-23 14:50:59 iss-user", color=colorspace::rainbow_hcl(5)[-1], cex=0.7, xlab="State_Region", ylab="Prevalence_Risk4")


if(!require(gplots)){install.packages("gplots")}
## Loading required package: gplots
## 
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
## 
##     lowess
library('gplots')

#=======================================================================
# Rattle timestamp: 2019-12-23 11:16:35 x86_64-pc-linux-gnu 

# The 'gplots' package provides the 'barplot2' function.

library(gplots, quietly=TRUE)

#=======================================================================
# Rattle timestamp: 2019-12-23 11:16:36 x86_64-pc-linux-gnu 

# Bar Plot 

# Generate the summary data for plotting.

ds <- rbind(summary(na.omit(crs$dataset[crs$train,]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="High",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Low",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Medium",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Very High",]$Source)))

# Sort the entries.

ord <- order(ds[1,], decreasing=TRUE)

# Plot the data.

bp <-  barplot2(ds[,ord], beside=TRUE, ylab="Frequency", xlab="Source", ylim=c(0, 715), col=colorspace::rainbow_hcl(5))

# Add the actual frequencies.

text(bp, ds[,ord]+24, ds[,ord])

# Add a legend to the plot.

legend("topright", bty="n", c("All","High","Low","Medium","Very High"),  fill=colorspace::rainbow_hcl(5))

# Add a title to the plot.

title(main="Distribution of Source (sample)\nby Prevalence_Risk4",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))


#=======================================================================
# Rattle timestamp: 2019-12-23 11:21:08 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(7,37),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'


#=======================================================================
# Rattle timestamp: 2019-12-23 11:25:27 x86_64-pc-linux-gnu 

# Display a pairs plot for the selected variables. 

# Use GGally's ggpairs() to do the hard work.

crs$dataset[crs$train,] %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  GGally::ggpairs(columns=c(3,7,37),
        mapping=ggplot2::aes(colour=Prevalence_Risk4, alpha=0.5),
                diag=list(continuous="density",
                          discrete="bar"),
                upper=list(continuous="cor",
                           combo="box",
                           discrete="ratio"),
                lower=list(continuous="points",
                           combo="denstrip",
                           discrete="facetbar")) +
  ggplot2::theme(panel.grid.major=ggplot2::element_blank())
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$continuous from 'density' to 'densityDiag'
## Warning in check_and_set_ggpairs_defaults("diag", diag, continuous =
## "densityDiag", : Changing diag$discrete from 'bar' to 'barDiag'
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 54 rows containing missing values (geom_bar).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 31 rows containing missing values (geom_bar).

<h3>
Rattle: EDA Explore & Test: Correlation
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 11:31:10 x86_64-pc-linux-gnu 

# Generate a correlation plot for the variables. 

# The 'corrplot' package provides the 'corrplot' function.

library(corrplot, quietly=TRUE)
## corrplot 0.84 loaded
# Correlations work for numeric variables only.

crs$cor <- cor(crs$dataset[crs$train, crs$numeric], use="pairwise", method="pearson")

# Order the correlations by their strength.

crs$ord <- order(crs$cor[1,])
crs$cor <- crs$cor[crs$ord, crs$ord]

# Display the actual correlations.

print(crs$cor)
##                                      Hispanic.Upper.CI
## Hispanic.Upper.CI                            1.0000000
## Asian.or.Pacific.Islander.Upper.CI           0.4298575
## Non.hispanic.black.Upper.CI                  0.5770878
## Female.Upper.CI                              0.7844853
## Chi_Wilson_Corrected_Upper.CI                0.8090598
## Upper.CI                                     0.8077450
## Hispanic.Prevalence                          0.8531290
## Prevalence                                   0.7801735
## Proportion                                   0.7797398
## Male.Upper.CI                                0.8151332
## Chi_Wilson_Corrected_Lower.CI                0.7467144
## Lower.CI                                     0.7468489
## Non.hispanic.black.Prevalence                0.6482372
## Non.hispanic.white.Upper.CI                  0.7183094
## Male.Prevalence                              0.7851024
## Hispanic.Lower.CI                            0.7130322
## Female.Prevalence                            0.7014905
## Year                                         0.4832048
## Year_Factor                                  0.4832048
## Male.Lower.CI                                0.7514020
## Non.hispanic.white.Prevalence                0.6744435
## Non.hispanic.black.Lower.CI                  0.6298063
## Non.hispanic.white.Lower.CI                  0.6240272
## Female.Lower.CI                              0.6155074
## Asian.or.Pacific.Islander.Prevalence         0.4003805
## Asian.or.Pacific.Islander.Lower.CI           0.3635529
## Numerator_ASD                                0.1063185
## Numerator_NonASD                            -0.4578654
## Denominator                                 -0.4508197
##                                      Asian.or.Pacific.Islander.Upper.CI
## Hispanic.Upper.CI                                             0.4298575
## Asian.or.Pacific.Islander.Upper.CI                            1.0000000
## Non.hispanic.black.Upper.CI                                   0.4492727
## Female.Upper.CI                                               0.5135291
## Chi_Wilson_Corrected_Upper.CI                                 0.4878682
## Upper.CI                                                      0.4891886
## Hispanic.Prevalence                                           0.4037482
## Prevalence                                                    0.4780977
## Proportion                                                    0.4776729
## Male.Upper.CI                                                 0.4814035
## Chi_Wilson_Corrected_Lower.CI                                 0.4658831
## Lower.CI                                                      0.4672622
## Non.hispanic.black.Prevalence                                 0.5091011
## Non.hispanic.white.Upper.CI                                   0.4858090
## Male.Prevalence                                               0.4707691
## Hispanic.Lower.CI                                             0.3828951
## Female.Prevalence                                             0.4821725
## Year                                                          0.3114580
## Year_Factor                                                   0.3114580
## Male.Lower.CI                                                 0.4601527
## Non.hispanic.white.Prevalence                                 0.4694430
## Non.hispanic.black.Lower.CI                                   0.4947086
## Non.hispanic.white.Lower.CI                                   0.4519968
## Female.Lower.CI                                               0.4422637
## Asian.or.Pacific.Islander.Prevalence                          0.6800537
## Asian.or.Pacific.Islander.Lower.CI                            0.5726997
## Numerator_ASD                                                 0.1740981
## Numerator_NonASD                                             -0.2791979
## Denominator                                                  -0.2731826
##                                      Non.hispanic.black.Upper.CI
## Hispanic.Upper.CI                                      0.5770878
## Asian.or.Pacific.Islander.Upper.CI                     0.4492727
## Non.hispanic.black.Upper.CI                            1.0000000
## Female.Upper.CI                                        0.8000430
## Chi_Wilson_Corrected_Upper.CI                          0.8059200
## Upper.CI                                               0.8055755
## Hispanic.Prevalence                                    0.7578635
## Prevalence                                             0.7874854
## Proportion                                             0.7873263
## Male.Upper.CI                                          0.8010181
## Chi_Wilson_Corrected_Lower.CI                          0.7662592
## Lower.CI                                               0.7665997
## Non.hispanic.black.Prevalence                          0.8973060
## Non.hispanic.white.Upper.CI                            0.8123196
## Male.Prevalence                                        0.7825046
## Hispanic.Lower.CI                                      0.7782561
## Female.Prevalence                                      0.7476920
## Year                                                   0.5254958
## Year_Factor                                            0.5254958
## Male.Lower.CI                                          0.7618531
## Non.hispanic.white.Prevalence                          0.7841707
## Non.hispanic.black.Lower.CI                            0.7746102
## Non.hispanic.white.Lower.CI                            0.7515534
## Female.Lower.CI                                        0.6885308
## Asian.or.Pacific.Islander.Prevalence                   0.5642913
## Asian.or.Pacific.Islander.Lower.CI                     0.5508371
## Numerator_ASD                                          0.3260676
## Numerator_NonASD                                      -0.2401915
## Denominator                                           -0.2321360
##                                      Female.Upper.CI
## Hispanic.Upper.CI                          0.7844853
## Asian.or.Pacific.Islander.Upper.CI         0.5135291
## Non.hispanic.black.Upper.CI                0.8000430
## Female.Upper.CI                            1.0000000
## Chi_Wilson_Corrected_Upper.CI              0.9458460
## Upper.CI                                   0.9456546
## Hispanic.Prevalence                        0.8657680
## Prevalence                                 0.9361990
## Proportion                                 0.9361048
## Male.Upper.CI                              0.9251909
## Chi_Wilson_Corrected_Lower.CI              0.9213684
## Lower.CI                                   0.9214256
## Non.hispanic.black.Prevalence              0.8601342
## Non.hispanic.white.Upper.CI                0.9092777
## Male.Prevalence                            0.9160548
## Hispanic.Lower.CI                          0.8393387
## Female.Prevalence                          0.9708281
## Year                                       0.7419132
## Year_Factor                                0.7419132
## Male.Lower.CI                              0.9011258
## Non.hispanic.white.Prevalence              0.8952741
## Non.hispanic.black.Lower.CI                0.8185917
## Non.hispanic.white.Lower.CI                0.8711692
## Female.Lower.CI                            0.9195566
## Asian.or.Pacific.Islander.Prevalence       0.6590192
## Asian.or.Pacific.Islander.Lower.CI         0.6279852
## Numerator_ASD                              0.4428578
## Numerator_NonASD                          -0.2167788
## Denominator                               -0.2071011
##                                      Chi_Wilson_Corrected_Upper.CI    Upper.CI
## Hispanic.Upper.CI                                       0.80905981  0.80774500
## Asian.or.Pacific.Islander.Upper.CI                      0.48786816  0.48918855
## Non.hispanic.black.Upper.CI                             0.80591997  0.80557548
## Female.Upper.CI                                         0.94584603  0.94565456
## Chi_Wilson_Corrected_Upper.CI                           1.00000000  0.99541262
## Upper.CI                                                0.99541262  1.00000000
## Hispanic.Prevalence                                     0.91516119  0.91454829
## Prevalence                                              0.97951767  0.96465789
## Proportion                                              0.97930627  0.96418866
## Male.Upper.CI                                           0.99752082  0.99738879
## Chi_Wilson_Corrected_Lower.CI                           0.91228106  0.88602921
## Lower.CI                                                0.88225955  0.84846980
## Non.hispanic.black.Prevalence                           0.88790865  0.88844237
## Non.hispanic.white.Upper.CI                             0.97207814  0.97212375
## Male.Prevalence                                         0.99507982  0.99537085
## Hispanic.Lower.CI                                       0.87917344  0.87927023
## Female.Prevalence                                       0.92996298  0.93080932
## Year                                                    0.58299884  0.55994064
## Year_Factor                                             0.58299884  0.55994064
## Male.Lower.CI                                           0.98519489  0.98585887
## Non.hispanic.white.Prevalence                           0.96193997  0.96251563
## Non.hispanic.black.Lower.CI                             0.86556683  0.86673094
## Non.hispanic.white.Lower.CI                             0.94019561  0.94119948
## Female.Lower.CI                                         0.88787147  0.88941605
## Asian.or.Pacific.Islander.Prevalence                    0.68478402  0.68714891
## Asian.or.Pacific.Islander.Lower.CI                      0.67774354  0.68027718
## Numerator_ASD                                           0.03465386  0.01816989
## Numerator_NonASD                                       -0.17958202 -0.17926413
## Denominator                                            -0.17815834 -0.17797036
##                                      Hispanic.Prevalence Prevalence Proportion
## Hispanic.Upper.CI                              0.8531290  0.7801735  0.7797398
## Asian.or.Pacific.Islander.Upper.CI             0.4037482  0.4780977  0.4776729
## Non.hispanic.black.Upper.CI                    0.7578635  0.7874854  0.7873263
## Female.Upper.CI                                0.8657680  0.9361990  0.9361048
## Chi_Wilson_Corrected_Upper.CI                  0.9151612  0.9795177  0.9793063
## Upper.CI                                       0.9145483  0.9646579  0.9641887
## Hispanic.Prevalence                            1.0000000  0.9075630  0.9073042
## Prevalence                                     0.9075630  1.0000000  0.9999644
## Proportion                                     0.9073042  0.9999644  1.0000000
## Male.Upper.CI                                  0.9130586  0.9912004  0.9910930
## Chi_Wilson_Corrected_Lower.CI                  0.8932551  0.9758906  0.9761892
## Lower.CI                                       0.8928560  0.9576820  0.9580889
## Non.hispanic.black.Prevalence                  0.8296154  0.8849879  0.8849095
## Non.hispanic.white.Upper.CI                    0.8825931  0.9712746  0.9711426
## Male.Prevalence                                0.9068690  0.9975709  0.9975493
## Hispanic.Lower.CI                              0.9668667  0.8835645  0.8833812
## Female.Prevalence                              0.8378239  0.9417238  0.9417901
## Year                                           0.6576727  0.6368602  0.6371841
## Year_Factor                                    0.6576727  0.6368602  0.6371841
## Male.Lower.CI                                  0.8934155  0.9953502  0.9954076
## Non.hispanic.white.Prevalence                  0.8562106  0.9720815  0.9721023
## Non.hispanic.black.Lower.CI                    0.7973316  0.8733330  0.8732782
## Non.hispanic.white.Lower.CI                    0.8221190  0.9593879  0.9595443
## Female.Lower.CI                                0.7887967  0.9138582  0.9140599
## Asian.or.Pacific.Islander.Prevalence           0.5543675  0.7175789  0.7178463
## Asian.or.Pacific.Islander.Lower.CI             0.5605431  0.7176723  0.7179792
## Numerator_ASD                                  0.4150610  0.1101324  0.1105209
## Numerator_NonASD                              -0.1794519 -0.1440062 -0.1438734
## Denominator                                   -0.1705785 -0.1422258 -0.1420909
##                                      Male.Upper.CI
## Hispanic.Upper.CI                        0.8151332
## Asian.or.Pacific.Islander.Upper.CI       0.4814035
## Non.hispanic.black.Upper.CI              0.8010181
## Female.Upper.CI                          0.9251909
## Chi_Wilson_Corrected_Upper.CI            0.9975208
## Upper.CI                                 0.9973888
## Hispanic.Prevalence                      0.9130586
## Prevalence                               0.9912004
## Proportion                               0.9910930
## Male.Upper.CI                            1.0000000
## Chi_Wilson_Corrected_Lower.CI            0.9784426
## Lower.CI                                 0.9787794
## Non.hispanic.black.Prevalence            0.8803381
## Non.hispanic.white.Upper.CI              0.9700115
## Male.Prevalence                          0.9952129
## Hispanic.Lower.CI                        0.8695569
## Female.Prevalence                        0.9029531
## Year                                     0.6974278
## Year_Factor                              0.6974278
## Male.Lower.CI                            0.9832614
## Non.hispanic.white.Prevalence            0.9561347
## Non.hispanic.black.Lower.CI              0.8587681
## Non.hispanic.white.Lower.CI              0.9313466
## Female.Lower.CI                          0.8571072
## Asian.or.Pacific.Islander.Prevalence     0.6684709
## Asian.or.Pacific.Islander.Lower.CI       0.6629791
## Numerator_ASD                            0.5112196
## Numerator_NonASD                        -0.1442297
## Denominator                             -0.1342816
##                                      Chi_Wilson_Corrected_Lower.CI    Lower.CI
## Hispanic.Upper.CI                                       0.74671443  0.74684890
## Asian.or.Pacific.Islander.Upper.CI                      0.46588312  0.46726224
## Non.hispanic.black.Upper.CI                             0.76625919  0.76659968
## Female.Upper.CI                                         0.92136843  0.92142564
## Chi_Wilson_Corrected_Upper.CI                           0.91228106  0.88225955
## Upper.CI                                                0.88602921  0.84846980
## Hispanic.Prevalence                                     0.89325505  0.89285598
## Prevalence                                              0.97589055  0.95768201
## Proportion                                              0.97618915  0.95808886
## Male.Upper.CI                                           0.97844259  0.97877945
## Chi_Wilson_Corrected_Lower.CI                           1.00000000  0.99603320
## Lower.CI                                                0.99603320  1.00000000
## Non.hispanic.black.Prevalence                           0.87679752  0.87784420
## Non.hispanic.white.Upper.CI                             0.96372938  0.96373813
## Male.Prevalence                                         0.99273412  0.99293262
## Hispanic.Lower.CI                                       0.88079929  0.88025118
## Female.Prevalence                                       0.94607324  0.94572840
## Year                                                    0.66981185  0.67445971
## Year_Factor                                             0.66981185  0.67445971
## Male.Lower.CI                                           0.99750176  0.99759142
## Non.hispanic.white.Prevalence                           0.97452706  0.97426835
## Non.hispanic.black.Lower.CI                             0.87461976  0.87594240
## Non.hispanic.white.Lower.CI                             0.97024727  0.96980780
## Female.Lower.CI                                         0.93127136  0.93062945
## Asian.or.Pacific.Islander.Prevalence                    0.74301825  0.74284991
## Asian.or.Pacific.Islander.Lower.CI                      0.74961248  0.74954762
## Numerator_ASD                                           0.19342032  0.21193828
## Numerator_NonASD                                       -0.09422197 -0.08580840
## Denominator                                            -0.09211574 -0.08361264
##                                      Non.hispanic.black.Prevalence
## Hispanic.Upper.CI                                       0.64823725
## Asian.or.Pacific.Islander.Upper.CI                      0.50910107
## Non.hispanic.black.Upper.CI                             0.89730595
## Female.Upper.CI                                         0.86013423
## Chi_Wilson_Corrected_Upper.CI                           0.88790865
## Upper.CI                                                0.88844237
## Hispanic.Prevalence                                     0.82961545
## Prevalence                                              0.88498793
## Proportion                                              0.88490954
## Male.Upper.CI                                           0.88033811
## Chi_Wilson_Corrected_Lower.CI                           0.87679752
## Lower.CI                                                0.87784420
## Non.hispanic.black.Prevalence                           1.00000000
## Non.hispanic.white.Upper.CI                             0.88462661
## Male.Prevalence                                         0.87887238
## Hispanic.Lower.CI                                       0.84217592
## Female.Prevalence                                       0.84706548
## Year                                                    0.62659411
## Year_Factor                                             0.62659411
## Male.Lower.CI                                           0.87223577
## Non.hispanic.white.Prevalence                           0.87018934
## Non.hispanic.black.Lower.CI                             0.97011491
## Non.hispanic.white.Lower.CI                             0.84659049
## Female.Lower.CI                                         0.81320804
## Asian.or.Pacific.Islander.Prevalence                    0.71073353
## Asian.or.Pacific.Islander.Lower.CI                      0.72358424
## Numerator_ASD                                           0.50594107
## Numerator_NonASD                                       -0.07211251
## Denominator                                            -0.06308227
##                                      Non.hispanic.white.Upper.CI
## Hispanic.Upper.CI                                     0.71830936
## Asian.or.Pacific.Islander.Upper.CI                    0.48580896
## Non.hispanic.black.Upper.CI                           0.81231956
## Female.Upper.CI                                       0.90927769
## Chi_Wilson_Corrected_Upper.CI                         0.97207814
## Upper.CI                                              0.97212375
## Hispanic.Prevalence                                   0.88259307
## Prevalence                                            0.97127456
## Proportion                                            0.97114263
## Male.Upper.CI                                         0.97001149
## Chi_Wilson_Corrected_Lower.CI                         0.96372938
## Lower.CI                                              0.96373813
## Non.hispanic.black.Prevalence                         0.88462661
## Non.hispanic.white.Upper.CI                           1.00000000
## Male.Prevalence                                       0.97129317
## Hispanic.Lower.CI                                     0.87701110
## Female.Prevalence                                     0.90085249
## Year                                                  0.66808127
## Year_Factor                                           0.66808127
## Male.Lower.CI                                         0.96454309
## Non.hispanic.white.Prevalence                         0.99111656
## Non.hispanic.black.Lower.CI                           0.85465487
## Non.hispanic.white.Lower.CI                           0.97065372
## Female.Lower.CI                                       0.86836808
## Asian.or.Pacific.Islander.Prevalence                  0.70902606
## Asian.or.Pacific.Islander.Lower.CI                    0.70645866
## Numerator_ASD                                         0.57006058
## Numerator_NonASD                                     -0.06334693
## Denominator                                          -0.05337890
##                                      Male.Prevalence Hispanic.Lower.CI
## Hispanic.Upper.CI                         0.78510238        0.71303219
## Asian.or.Pacific.Islander.Upper.CI        0.47076911        0.38289515
## Non.hispanic.black.Upper.CI               0.78250456        0.77825612
## Female.Upper.CI                           0.91605476        0.83933869
## Chi_Wilson_Corrected_Upper.CI             0.99507982        0.87917344
## Upper.CI                                  0.99537085        0.87927023
## Hispanic.Prevalence                       0.90686904        0.96686666
## Prevalence                                0.99757087        0.88356446
## Proportion                                0.99754932        0.88338124
## Male.Upper.CI                             0.99521291        0.86955687
## Chi_Wilson_Corrected_Lower.CI             0.99273412        0.88079929
## Lower.CI                                  0.99293262        0.88025118
## Non.hispanic.black.Prevalence             0.87887238        0.84217592
## Non.hispanic.white.Upper.CI               0.97129317        0.87701110
## Male.Prevalence                           1.00000000        0.87646754
## Hispanic.Lower.CI                         0.87646754        1.00000000
## Female.Prevalence                         0.91681912        0.84253365
## Year                                      0.70937139        0.65945595
## Year_Factor                               0.70937139        0.65945595
## Male.Lower.CI                             0.99632259        0.87501764
## Non.hispanic.white.Prevalence             0.96924001        0.86482489
## Non.hispanic.black.Lower.CI               0.86881485        0.80492048
## Non.hispanic.white.Lower.CI               0.95419767        0.84316419
## Female.Lower.CI                           0.88632958        0.81795017
## Asian.or.Pacific.Islander.Prevalence      0.70443879        0.59514051
## Asian.or.Pacific.Islander.Lower.CI        0.70691752        0.61949233
## Numerator_ASD                             0.58634823        0.53247480
## Numerator_NonASD                         -0.05861261       -0.03026967
## Denominator                              -0.04843529       -0.02120298
##                                      Female.Prevalence       Year Year_Factor
## Hispanic.Upper.CI                           0.70149049 0.48320479  0.48320479
## Asian.or.Pacific.Islander.Upper.CI          0.48217250 0.31145797  0.31145797
## Non.hispanic.black.Upper.CI                 0.74769197 0.52549580  0.52549580
## Female.Upper.CI                             0.97082808 0.74191323  0.74191323
## Chi_Wilson_Corrected_Upper.CI               0.92996298 0.58299884  0.58299884
## Upper.CI                                    0.93080932 0.55994064  0.55994064
## Hispanic.Prevalence                         0.83782393 0.65767269  0.65767269
## Prevalence                                  0.94172383 0.63686023  0.63686023
## Proportion                                  0.94179011 0.63718406  0.63718406
## Male.Upper.CI                               0.90295306 0.69742781  0.69742781
## Chi_Wilson_Corrected_Lower.CI               0.94607324 0.66981185  0.66981185
## Lower.CI                                    0.94572840 0.67445971  0.67445971
## Non.hispanic.black.Prevalence               0.84706548 0.62659411  0.62659411
## Non.hispanic.white.Upper.CI                 0.90085249 0.66808127  0.66808127
## Male.Prevalence                             0.91681912 0.70937139  0.70937139
## Hispanic.Lower.CI                           0.84253365 0.65945595  0.65945595
## Female.Prevalence                           1.00000000 0.76514844  0.76514844
## Year                                        0.76514844 1.00000000  1.00000000
## Year_Factor                                 0.76514844 1.00000000  1.00000000
## Male.Lower.CI                               0.92200420 0.71540318  0.71540318
## Non.hispanic.white.Prevalence               0.91561783 0.68139125  0.68139125
## Non.hispanic.black.Lower.CI                 0.83351227 0.61981346  0.61981346
## Non.hispanic.white.Lower.CI                 0.91549287 0.68643036  0.68643036
## Female.Lower.CI                             0.98603079 0.75373781  0.75373781
## Asian.or.Pacific.Islander.Prevalence        0.74023039 0.53165911  0.53165911
## Asian.or.Pacific.Islander.Lower.CI          0.72714352 0.53479769  0.53479769
## Numerator_ASD                               0.61548685 0.28851248  0.28851248
## Numerator_NonASD                           -0.01366226 0.01790509  0.01790509
## Denominator                                -0.00353157 0.02002784  0.02002784
##                                      Male.Lower.CI
## Hispanic.Upper.CI                       0.75140198
## Asian.or.Pacific.Islander.Upper.CI      0.46015270
## Non.hispanic.black.Upper.CI             0.76185305
## Female.Upper.CI                         0.90112582
## Chi_Wilson_Corrected_Upper.CI           0.98519489
## Upper.CI                                0.98585887
## Hispanic.Prevalence                     0.89341554
## Prevalence                              0.99535016
## Proportion                              0.99540761
## Male.Upper.CI                           0.98326138
## Chi_Wilson_Corrected_Lower.CI           0.99750176
## Lower.CI                                0.99759142
## Non.hispanic.black.Prevalence           0.87223577
## Non.hispanic.white.Upper.CI             0.96454309
## Male.Prevalence                         0.99632259
## Hispanic.Lower.CI                       0.87501764
## Female.Prevalence                       0.92200420
## Year                                    0.71540318
## Year_Factor                             0.71540318
## Male.Lower.CI                           1.00000000
## Non.hispanic.white.Prevalence           0.97286632
## Non.hispanic.black.Lower.CI             0.87234856
## Non.hispanic.white.Lower.CI             0.96656152
## Female.Lower.CI                         0.90511927
## Asian.or.Pacific.Islander.Prevalence    0.73303734
## Asian.or.Pacific.Islander.Lower.CI      0.74245831
## Numerator_ASD                           0.64863675
## Numerator_NonASD                        0.01564790
## Denominator                             0.02597746
##                                      Non.hispanic.white.Prevalence
## Hispanic.Upper.CI                                       0.67444346
## Asian.or.Pacific.Islander.Upper.CI                      0.46944298
## Non.hispanic.black.Upper.CI                             0.78417074
## Female.Upper.CI                                         0.89527410
## Chi_Wilson_Corrected_Upper.CI                           0.96193997
## Upper.CI                                                0.96251563
## Hispanic.Prevalence                                     0.85621056
## Prevalence                                              0.97208151
## Proportion                                              0.97210234
## Male.Upper.CI                                           0.95613470
## Chi_Wilson_Corrected_Lower.CI                           0.97452706
## Lower.CI                                                0.97426835
## Non.hispanic.black.Prevalence                           0.87018934
## Non.hispanic.white.Upper.CI                             0.99111656
## Male.Prevalence                                         0.96924001
## Hispanic.Lower.CI                                       0.86482489
## Female.Prevalence                                       0.91561783
## Year                                                    0.68139125
## Year_Factor                                             0.68139125
## Male.Lower.CI                                           0.97286632
## Non.hispanic.white.Prevalence                           1.00000000
## Non.hispanic.black.Lower.CI                             0.85093836
## Non.hispanic.white.Lower.CI                             0.99381747
## Female.Lower.CI                                         0.90244962
## Asian.or.Pacific.Islander.Prevalence                    0.75097384
## Asian.or.Pacific.Islander.Lower.CI                      0.75347604
## Numerator_ASD                                           0.65584599
## Numerator_NonASD                                        0.03406378
## Denominator                                             0.04429761
##                                      Non.hispanic.black.Lower.CI
## Hispanic.Upper.CI                                     0.62980631
## Asian.or.Pacific.Islander.Upper.CI                    0.49470864
## Non.hispanic.black.Upper.CI                           0.77461021
## Female.Upper.CI                                       0.81859170
## Chi_Wilson_Corrected_Upper.CI                         0.86556683
## Upper.CI                                              0.86673094
## Hispanic.Prevalence                                   0.79733159
## Prevalence                                            0.87333297
## Proportion                                            0.87327819
## Male.Upper.CI                                         0.85876813
## Chi_Wilson_Corrected_Lower.CI                         0.87461976
## Lower.CI                                              0.87594240
## Non.hispanic.black.Prevalence                         0.97011491
## Non.hispanic.white.Upper.CI                           0.85465487
## Male.Prevalence                                       0.86881485
## Hispanic.Lower.CI                                     0.80492048
## Female.Prevalence                                     0.83351227
## Year                                                  0.61981346
## Year_Factor                                           0.61981346
## Male.Lower.CI                                         0.87234856
## Non.hispanic.white.Prevalence                         0.85093836
## Non.hispanic.black.Lower.CI                           1.00000000
## Non.hispanic.white.Lower.CI                           0.83622377
## Female.Lower.CI                                       0.81831756
## Asian.or.Pacific.Islander.Prevalence                  0.74469169
## Asian.or.Pacific.Islander.Lower.CI                    0.77706662
## Numerator_ASD                                         0.58678898
## Numerator_NonASD                                      0.04335028
## Denominator                                           0.05235798
##                                      Non.hispanic.white.Lower.CI
## Hispanic.Upper.CI                                      0.6240272
## Asian.or.Pacific.Islander.Upper.CI                     0.4519968
## Non.hispanic.black.Upper.CI                            0.7515534
## Female.Upper.CI                                        0.8711692
## Chi_Wilson_Corrected_Upper.CI                          0.9401956
## Upper.CI                                               0.9411995
## Hispanic.Prevalence                                    0.8221190
## Prevalence                                             0.9593879
## Proportion                                             0.9595443
## Male.Upper.CI                                          0.9313466
## Chi_Wilson_Corrected_Lower.CI                          0.9702473
## Lower.CI                                               0.9698078
## Non.hispanic.black.Prevalence                          0.8465905
## Non.hispanic.white.Upper.CI                            0.9706537
## Male.Prevalence                                        0.9541977
## Hispanic.Lower.CI                                      0.8431642
## Female.Prevalence                                      0.9154929
## Year                                                   0.6864304
## Year_Factor                                            0.6864304
## Male.Lower.CI                                          0.9665615
## Non.hispanic.white.Prevalence                          0.9938175
## Non.hispanic.black.Lower.CI                            0.8362238
## Non.hispanic.white.Lower.CI                            1.0000000
## Female.Lower.CI                                        0.9187423
## Asian.or.Pacific.Islander.Prevalence                   0.7765136
## Asian.or.Pacific.Islander.Lower.CI                     0.7826060
## Numerator_ASD                                          0.7210445
## Numerator_NonASD                                       0.1159009
## Denominator                                            0.1262467
##                                      Female.Lower.CI
## Hispanic.Upper.CI                          0.6155074
## Asian.or.Pacific.Islander.Upper.CI         0.4422637
## Non.hispanic.black.Upper.CI                0.6885308
## Female.Upper.CI                            0.9195566
## Chi_Wilson_Corrected_Upper.CI              0.8878715
## Upper.CI                                   0.8894161
## Hispanic.Prevalence                        0.7887967
## Prevalence                                 0.9138582
## Proportion                                 0.9140599
## Male.Upper.CI                              0.8571072
## Chi_Wilson_Corrected_Lower.CI              0.9312714
## Lower.CI                                   0.9306294
## Non.hispanic.black.Prevalence              0.8132080
## Non.hispanic.white.Upper.CI                0.8683681
## Male.Prevalence                            0.8863296
## Hispanic.Lower.CI                          0.8179502
## Female.Prevalence                          0.9860308
## Year                                       0.7537378
## Year_Factor                                0.7537378
## Male.Lower.CI                              0.9051193
## Non.hispanic.white.Prevalence              0.9024496
## Non.hispanic.black.Lower.CI                0.8183176
## Non.hispanic.white.Lower.CI                0.9187423
## Female.Lower.CI                            1.0000000
## Asian.or.Pacific.Islander.Prevalence       0.7654995
## Asian.or.Pacific.Islander.Lower.CI         0.7658045
## Numerator_ASD                              0.7176094
## Numerator_NonASD                           0.1326307
## Denominator                                0.1427277
##                                      Asian.or.Pacific.Islander.Prevalence
## Hispanic.Upper.CI                                               0.4003805
## Asian.or.Pacific.Islander.Upper.CI                              0.6800537
## Non.hispanic.black.Upper.CI                                     0.5642913
## Female.Upper.CI                                                 0.6590192
## Chi_Wilson_Corrected_Upper.CI                                   0.6847840
## Upper.CI                                                        0.6871489
## Hispanic.Prevalence                                             0.5543675
## Prevalence                                                      0.7175789
## Proportion                                                      0.7178463
## Male.Upper.CI                                                   0.6684709
## Chi_Wilson_Corrected_Lower.CI                                   0.7430182
## Lower.CI                                                        0.7428499
## Non.hispanic.black.Prevalence                                   0.7107335
## Non.hispanic.white.Upper.CI                                     0.7090261
## Male.Prevalence                                                 0.7044388
## Hispanic.Lower.CI                                               0.5951405
## Female.Prevalence                                               0.7402304
## Year                                                            0.5316591
## Year_Factor                                                     0.5316591
## Male.Lower.CI                                                   0.7330373
## Non.hispanic.white.Prevalence                                   0.7509738
## Non.hispanic.black.Lower.CI                                     0.7446917
## Non.hispanic.white.Lower.CI                                     0.7765136
## Female.Lower.CI                                                 0.7654995
## Asian.or.Pacific.Islander.Prevalence                            1.0000000
## Asian.or.Pacific.Islander.Lower.CI                              0.9794687
## Numerator_ASD                                                   0.6769568
## Numerator_NonASD                                                0.1803188
## Denominator                                                     0.1892436
##                                      Asian.or.Pacific.Islander.Lower.CI
## Hispanic.Upper.CI                                             0.3635529
## Asian.or.Pacific.Islander.Upper.CI                            0.5726997
## Non.hispanic.black.Upper.CI                                   0.5508371
## Female.Upper.CI                                               0.6279852
## Chi_Wilson_Corrected_Upper.CI                                 0.6777435
## Upper.CI                                                      0.6802772
## Hispanic.Prevalence                                           0.5605431
## Prevalence                                                    0.7176723
## Proportion                                                    0.7179792
## Male.Upper.CI                                                 0.6629791
## Chi_Wilson_Corrected_Lower.CI                                 0.7496125
## Lower.CI                                                      0.7495476
## Non.hispanic.black.Prevalence                                 0.7235842
## Non.hispanic.white.Upper.CI                                   0.7064587
## Male.Prevalence                                               0.7069175
## Hispanic.Lower.CI                                             0.6194923
## Female.Prevalence                                             0.7271435
## Year                                                          0.5347977
## Year_Factor                                                   0.5347977
## Male.Lower.CI                                                 0.7424583
## Non.hispanic.white.Prevalence                                 0.7534760
## Non.hispanic.black.Lower.CI                                   0.7770666
## Non.hispanic.white.Lower.CI                                   0.7826060
## Female.Lower.CI                                               0.7658045
## Asian.or.Pacific.Islander.Prevalence                          0.9794687
## Asian.or.Pacific.Islander.Lower.CI                            1.0000000
## Numerator_ASD                                                 0.7514336
## Numerator_NonASD                                              0.2863726
## Denominator                                                   0.2952942
##                                      Numerator_ASD Numerator_NonASD Denominator
## Hispanic.Upper.CI                       0.10631851      -0.45786543 -0.45081970
## Asian.or.Pacific.Islander.Upper.CI      0.17409815      -0.27919788 -0.27318262
## Non.hispanic.black.Upper.CI             0.32606764      -0.24019149 -0.23213601
## Female.Upper.CI                         0.44285775      -0.21677882 -0.20710115
## Chi_Wilson_Corrected_Upper.CI           0.03465386      -0.17958202 -0.17815834
## Upper.CI                                0.01816989      -0.17926413 -0.17797036
## Hispanic.Prevalence                     0.41506099      -0.17945192 -0.17057853
## Prevalence                              0.11013238      -0.14400619 -0.14222583
## Proportion                              0.11052092      -0.14387344 -0.14209092
## Male.Upper.CI                           0.51121963      -0.14422973 -0.13428165
## Chi_Wilson_Corrected_Lower.CI           0.19342032      -0.09422197 -0.09211574
## Lower.CI                                0.21193828      -0.08580840 -0.08361264
## Non.hispanic.black.Prevalence           0.50594107      -0.07211251 -0.06308227
## Non.hispanic.white.Upper.CI             0.57006058      -0.06334693 -0.05337890
## Male.Prevalence                         0.58634823      -0.05861261 -0.04843529
## Hispanic.Lower.CI                       0.53247480      -0.03026967 -0.02120298
## Female.Prevalence                       0.61548685      -0.01366226 -0.00353157
## Year                                    0.28851248       0.01790509  0.02002784
## Year_Factor                             0.28851248       0.01790509  0.02002784
## Male.Lower.CI                           0.64863675       0.01564790  0.02597746
## Non.hispanic.white.Prevalence           0.65584599       0.03406378  0.04429761
## Non.hispanic.black.Lower.CI             0.58678898       0.04335028  0.05235798
## Non.hispanic.white.Lower.CI             0.72104448       0.11590094  0.12624673
## Female.Lower.CI                         0.71760943       0.13263067  0.14272772
## Asian.or.Pacific.Islander.Prevalence    0.67695675       0.18031877  0.18924362
## Asian.or.Pacific.Islander.Lower.CI      0.75143363       0.28637260  0.29529424
## Numerator_ASD                           1.00000000       0.82786736  0.83030005
## Numerator_NonASD                        0.82786736       1.00000000  0.99999053
## Denominator                             0.83030005       0.99999053  1.00000000
# Graphically display the correlations.

corrplot(crs$cor, mar=c(0,0,1,0))
title(main="Correlation ADV_ASD_State_R.csv using Pearson",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))


#=======================================================================
# Rattle timestamp: 2019-12-23 11:32:46 x86_64-pc-linux-gnu 

# Hierarchical Variable Correlation 

# Generate the correlations (numerics only).

cc <- cor(crs$dataset[crs$train, crs$numeric], use="pairwise", method="pearson")

# Generate hierarchical cluster of variables.

hc <- hclust(dist(cc), method="average")

# Generate the dendrogram.

dn <- as.dendrogram(hc)

# Now draw the dendrogram.

op <- par(mar = c(3, 4, 3, 10.86))
plot(dn, horiz = TRUE, nodePar = list(col = 3:2, cex = c(2.0, 0.75), pch = 21:22, bg=  c("light blue", "pink"), lab.cex = 0.75, lab.col = "tomato"), edgePar = list(col = "gray", lwd = 2), xlab="Height")
title(main="Variable Correlation Clusters
 ADV_ASD_State_R.csv using Pearson",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

par(op)

#=======================================================================
# Rattle timestamp: 2019-12-23 11:33:55 x86_64-pc-linux-gnu 

# Hierarchical Variable Correlation 

# Generate the correlations (numerics only).

cc <- cor(crs$dataset[crs$train, crs$numeric], use="pairwise", method="spearman")

# Generate hierarchical cluster of variables.

hc <- hclust(dist(cc), method="average")

# Generate the dendrogram.

dn <- as.dendrogram(hc)

# Now draw the dendrogram.

op <- par(mar = c(3, 4, 3, 10.86))
plot(dn, horiz = TRUE, nodePar = list(col = 3:2, cex = c(2.0, 0.75), pch = 21:22, bg=  c("light blue", "pink"), lab.cex = 0.75, lab.col = "tomato"), edgePar = list(col = "gray", lwd = 2), xlab="Height")
title(main="Variable Correlation Clusters
 ADV_ASD_State_R.csv using Spearman",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

par(op)

#=======================================================================
# Rattle timestamp: 2019-12-23 11:36:12 x86_64-pc-linux-gnu 

# Principal Components Analysis (on numerics only).

pc <- prcomp(na.omit(crs$dataset[crs$train, crs$numeric]), scale=TRUE, center=TRUE, tol=0)

# Show the output of the analysis.

pc
## Standard deviations (1, .., p=29):
##  [1] 4.656380e+00 1.820987e+00 1.112265e+00 9.545395e-01 7.437407e-01
##  [6] 6.229362e-01 5.188450e-01 4.828164e-01 4.237121e-01 3.097548e-01
## [11] 2.296600e-01 2.174858e-01 1.414526e-01 8.282109e-02 6.362457e-02
## [16] 4.164272e-02 2.967576e-02 2.474057e-02 1.782267e-02 1.467028e-02
## [21] 9.427596e-03 4.767943e-03 3.824069e-03 2.852320e-03 1.504068e-03
## [26] 1.408651e-03 5.042372e-04 5.196008e-16 4.246809e-16
## 
## Rotation (n x k) = (29 x 29):
##                                              PC1          PC2          PC3
## Denominator                           0.01883922  0.534519219 -0.085620632
## Prevalence                           -0.21289953 -0.023107040 -0.044421446
## Lower.CI                             -0.21278276  0.019630807 -0.046621564
## Upper.CI                             -0.21143642 -0.067635880 -0.037749486
## Year                                 -0.16313959  0.052170196 -0.295735159
## Numerator_ASD                        -0.12486026  0.429738087 -0.033616427
## Numerator_NonASD                      0.02110653  0.533643140 -0.086058432
## Proportion                           -0.21289857 -0.022459211 -0.044693299
## Chi_Wilson_Corrected_Lower.CI        -0.21274240  0.020491372 -0.047530630
## Chi_Wilson_Corrected_Upper.CI        -0.21131533 -0.069678448 -0.039744353
## Male.Prevalence                      -0.21126548 -0.030291026 -0.042247179
## Male.Lower.CI                        -0.21147726  0.015260084 -0.044112987
## Male.Upper.CI                        -0.20911867 -0.080769665 -0.036546949
## Female.Prevalence                    -0.20491117  0.017178848 -0.045737385
## Female.Lower.CI                      -0.19893453  0.103836861 -0.054750475
## Female.Upper.CI                      -0.20270439 -0.106994603 -0.030503649
## Non.hispanic.white.Prevalence        -0.20854472  0.026842891  0.005428251
## Non.hispanic.white.Lower.CI          -0.20608534  0.079646512  0.001663977
## Non.hispanic.white.Upper.CI          -0.20772011 -0.034053107  0.010456680
## Non.hispanic.black.Prevalence        -0.19617202 -0.019377626  0.113369069
## Non.hispanic.black.Lower.CI          -0.19374133  0.051269130  0.112866298
## Non.hispanic.black.Upper.CI          -0.17164747 -0.128213056  0.117208720
## Hispanic.Prevalence                  -0.19507691 -0.093902392 -0.138053874
## Hispanic.Lower.CI                    -0.19350606 -0.009150503 -0.128076228
## Hispanic.Upper.CI                    -0.16406062 -0.249515422 -0.070732375
## Asian.or.Pacific.Islander.Prevalence -0.16511852  0.186374164  0.428834481
## Asian.or.Pacific.Islander.Lower.CI   -0.16484185  0.238538542  0.357515379
## Asian.or.Pacific.Islander.Upper.CI   -0.11247202 -0.086381558  0.628543805
## Year_Factor                          -0.16313959  0.052170196 -0.295735159
##                                              PC4          PC5          PC6
## Denominator                           0.13006110 -0.000547975  0.166870856
## Prevalence                            0.06068929  0.090738907 -0.073546273
## Lower.CI                              0.05275986  0.101457125 -0.073758717
## Upper.CI                              0.06728518  0.074666719 -0.075311476
## Year                                 -0.56013012 -0.124729167  0.022734419
## Numerator_ASD                         0.02768358  0.081931308 -0.022580182
## Numerator_NonASD                      0.13110993 -0.001899198  0.169170209
## Proportion                            0.06073237  0.090914263 -0.074116672
## Chi_Wilson_Corrected_Lower.CI         0.05441440  0.103705871 -0.073084381
## Chi_Wilson_Corrected_Upper.CI         0.06654677  0.073913028 -0.075794989
## Male.Prevalence                       0.09519737  0.099806051 -0.085868341
## Male.Lower.CI                         0.08826241  0.111886901 -0.084128106
## Male.Upper.CI                         0.09815852  0.081605189 -0.086855604
## Female.Prevalence                    -0.12706360  0.065243472 -0.007783897
## Female.Lower.CI                      -0.13103919  0.085644133 -0.003065632
## Female.Upper.CI                      -0.10314789  0.018032303 -0.015818325
## Non.hispanic.white.Prevalence         0.10611025  0.035777997 -0.234772116
## Non.hispanic.white.Lower.CI           0.08452739  0.063031411 -0.265053266
## Non.hispanic.white.Upper.CI           0.12276363 -0.001866054 -0.191530948
## Non.hispanic.black.Prevalence         0.09082343 -0.447125717  0.086159462
## Non.hispanic.black.Lower.CI           0.08843075 -0.298594683  0.157857637
## Non.hispanic.black.Upper.CI           0.12576596 -0.625142200 -0.102380141
## Hispanic.Prevalence                   0.13646654 -0.010458977  0.463327604
## Hispanic.Lower.CI                     0.12953783 -0.164261326  0.448845836
## Hispanic.Upper.CI                     0.12194201  0.356593997  0.431881642
## Asian.or.Pacific.Islander.Prevalence -0.14707602  0.064514633 -0.040288748
## Asian.or.Pacific.Islander.Lower.CI   -0.07057439 -0.005160568 -0.018018820
## Asian.or.Pacific.Islander.Upper.CI   -0.32074045  0.170141543  0.277654701
## Year_Factor                          -0.56013012 -0.124729167  0.022734419
##                                               PC7         PC8          PC9
## Denominator                          -0.010129798  0.01031003 -0.116285200
## Prevalence                           -0.040024284  0.05183166 -0.027887084
## Lower.CI                             -0.026535942  0.04440401 -0.038678450
## Upper.CI                             -0.053885726  0.06413921 -0.025548128
## Year                                 -0.172151862  0.08878737  0.057035042
## Numerator_ASD                        -0.072626539 -0.12952164 -0.141692302
## Numerator_NonASD                     -0.009054726  0.01255527 -0.115303374
## Proportion                           -0.039827173  0.05161058 -0.028206472
## Chi_Wilson_Corrected_Lower.CI        -0.024216220  0.03764132 -0.034993374
## Chi_Wilson_Corrected_Upper.CI        -0.056836093  0.06468696 -0.021474415
## Male.Prevalence                      -0.139771969  0.10321855 -0.005972763
## Male.Lower.CI                        -0.127549634  0.09164722 -0.012152486
## Male.Upper.CI                        -0.154542814  0.11723615  0.004485658
## Female.Prevalence                     0.472486036 -0.16495384 -0.095429277
## Female.Lower.CI                       0.496874492 -0.20014166 -0.135811528
## Female.Upper.CI                       0.415314970 -0.11670867 -0.089792078
## Non.hispanic.white.Prevalence        -0.121646421 -0.14475969 -0.041643316
## Non.hispanic.white.Lower.CI          -0.090180806 -0.17809223 -0.060049504
## Non.hispanic.white.Upper.CI          -0.172878991 -0.11630782 -0.024238834
## Non.hispanic.black.Prevalence         0.085151860  0.27034505 -0.177536726
## Non.hispanic.black.Lower.CI           0.103270322  0.55772187 -0.240767607
## Non.hispanic.black.Upper.CI           0.029542985 -0.30832043  0.068668769
## Hispanic.Prevalence                  -0.131902737 -0.16583464  0.192441184
## Hispanic.Lower.CI                    -0.148358436 -0.39253247  0.153537958
## Hispanic.Upper.CI                     0.160627876  0.22848566  0.119752026
## Asian.or.Pacific.Islander.Prevalence  0.077067808  0.02463450  0.462649288
## Asian.or.Pacific.Islander.Lower.CI    0.057813986  0.14298308  0.527811356
## Asian.or.Pacific.Islander.Upper.CI   -0.276143703 -0.19034426 -0.487510254
## Year_Factor                          -0.172151862  0.08878737  0.057035042
##                                             PC10         PC11         PC12
## Denominator                           0.06879289 -0.204858242  0.306101859
## Prevalence                            0.08200198  0.108497013  0.102048377
## Lower.CI                              0.10552047  0.144822912  0.030137873
## Upper.CI                              0.06239574  0.090022561  0.154301779
## Year                                  0.02191142 -0.106528813 -0.004035175
## Numerator_ASD                         0.25781401  0.225147275 -0.698819674
## Numerator_NonASD                      0.06535603 -0.210921762  0.321110817
## Proportion                            0.08449622  0.107526509  0.101270728
## Chi_Wilson_Corrected_Lower.CI         0.10715588  0.136087129  0.040535307
## Chi_Wilson_Corrected_Upper.CI         0.06015092  0.081958073  0.157607660
## Male.Prevalence                       0.11475832  0.111955031  0.115743953
## Male.Lower.CI                         0.14442775  0.144094888  0.042210975
## Male.Upper.CI                         0.09105546  0.078377821  0.176819897
## Female.Prevalence                    -0.04220706  0.052948070  0.061202852
## Female.Lower.CI                      -0.03683131  0.067266257 -0.047254132
## Female.Upper.CI                      -0.10450224 -0.002849421  0.177915102
## Non.hispanic.white.Prevalence        -0.27568441 -0.308813304 -0.112622516
## Non.hispanic.white.Lower.CI          -0.17843052 -0.301326168 -0.186150314
## Non.hispanic.white.Upper.CI          -0.38060465 -0.303740383 -0.019927405
## Non.hispanic.black.Prevalence        -0.08081971 -0.085081351 -0.069582744
## Non.hispanic.black.Lower.CI          -0.27398030  0.111103628 -0.164142804
## Non.hispanic.black.Upper.CI           0.55480232 -0.192388405  0.035373115
## Hispanic.Prevalence                  -0.11950679  0.029099866 -0.006496903
## Hispanic.Lower.CI                    -0.26989196  0.300917136 -0.004190010
## Hispanic.Upper.CI                     0.29183833 -0.521829763 -0.250830920
## Asian.or.Pacific.Islander.Prevalence -0.01042384 -0.077261176  0.069975461
## Asian.or.Pacific.Islander.Lower.CI   -0.06619036  0.102506026 -0.037648503
## Asian.or.Pacific.Islander.Upper.CI    0.06566645 -0.023102263  0.093823642
## Year_Factor                           0.02191142 -0.106528813 -0.004035175
##                                              PC13          PC14         PC15
## Denominator                          -0.028599434  0.0270144770 -0.004946558
## Prevalence                            0.039494416  0.0092839324 -0.022046889
## Lower.CI                              0.196290298  0.0417503305 -0.029841077
## Upper.CI                             -0.156242573 -0.0391187810 -0.057772058
## Year                                  0.000984494  0.0205156999 -0.009718609
## Numerator_ASD                        -0.344034686 -0.1383112919  0.013492590
## Numerator_NonASD                     -0.023282713  0.0295970699 -0.005225209
## Proportion                            0.040686270  0.0003362093 -0.024603965
## Chi_Wilson_Corrected_Lower.CI         0.206479323  0.0319149729 -0.009473885
## Chi_Wilson_Corrected_Upper.CI        -0.167161271 -0.0443833446 -0.044808119
## Male.Prevalence                       0.016253350 -0.0039053767  0.010055068
## Male.Lower.CI                         0.187077542  0.0275497188  0.027036530
## Male.Upper.CI                        -0.199619691 -0.0500041083  0.001362240
## Female.Prevalence                     0.006194278  0.0304833327  0.129835700
## Female.Lower.CI                       0.374005144  0.0941052510  0.101131456
## Female.Upper.CI                      -0.555618868 -0.0973994655 -0.098370351
## Non.hispanic.white.Prevalence         0.048457685  0.0611828929 -0.052681215
## Non.hispanic.white.Lower.CI           0.320072884 -0.0678311534 -0.094486462
## Non.hispanic.white.Upper.CI          -0.302346841  0.1287850134  0.201693679
## Non.hispanic.black.Prevalence         0.083983957 -0.2267386899 -0.327262803
## Non.hispanic.black.Lower.CI           0.023580054  0.0619276048  0.209080157
## Non.hispanic.black.Upper.CI          -0.010647968  0.1185171536  0.142782340
## Hispanic.Prevalence                   0.066385200 -0.3256732175  0.635128151
## Hispanic.Lower.CI                     0.024393769  0.1678825393 -0.505020559
## Hispanic.Upper.CI                    -0.028855748  0.1436034280 -0.185783432
## Asian.or.Pacific.Islander.Prevalence  0.059604420 -0.6008138848 -0.152016060
## Asian.or.Pacific.Islander.Lower.CI   -0.080170229  0.5753533014  0.115527955
## Asian.or.Pacific.Islander.Upper.CI    0.007633103  0.0918037129  0.039679874
## Year_Factor                           0.000984494  0.0205156999 -0.009718609
##                                              PC16          PC17          PC18
## Denominator                          -0.008083713 -0.0132885096 -0.0065189945
## Prevalence                            0.041555402  0.0237709570  0.0073178907
## Lower.CI                              0.037851762  0.0973532148 -0.2184959890
## Upper.CI                              0.051166585 -0.0683002713  0.2179631810
## Year                                 -0.014153980 -0.0006141133  0.0031035281
## Numerator_ASD                         0.037038112  0.0424090895  0.0112373839
## Numerator_NonASD                     -0.008785119 -0.0141382375 -0.0067788013
## Proportion                            0.058216884  0.0089127905  0.0040249981
## Chi_Wilson_Corrected_Lower.CI         0.054446295  0.0670072023 -0.1426692805
## Chi_Wilson_Corrected_Upper.CI         0.085340034 -0.0856427532  0.1943057959
## Male.Prevalence                      -0.082973445  0.0510492860 -0.0311419096
## Male.Lower.CI                        -0.100506440  0.0925404929 -0.1807782251
## Male.Upper.CI                        -0.064116573 -0.0734776455  0.1930453229
## Female.Prevalence                    -0.096475857  0.0359987445 -0.6266391351
## Female.Lower.CI                       0.014575343  0.2502106274  0.6081448588
## Female.Upper.CI                       0.085051136 -0.2962763708  0.0098664036
## Non.hispanic.white.Prevalence         0.012799366 -0.0789027769 -0.0154645966
## Non.hispanic.white.Lower.CI           0.043749438 -0.5661168402 -0.0059247844
## Non.hispanic.white.Upper.CI          -0.112311058  0.5796533770 -0.0139952343
## Non.hispanic.black.Prevalence         0.591649447  0.2294286918 -0.0866916983
## Non.hispanic.black.Lower.CI          -0.477816872 -0.1978751190  0.0577146930
## Non.hispanic.black.Upper.CI          -0.189794733 -0.0360389870  0.0314934348
## Hispanic.Prevalence                   0.268992704 -0.1134328125 -0.0002169157
## Hispanic.Lower.CI                    -0.226463278  0.0082260375  0.0001481337
## Hispanic.Upper.CI                    -0.076474510  0.0447624616  0.0009104982
## Asian.or.Pacific.Islander.Prevalence -0.293575043  0.1287074652  0.0208246728
## Asian.or.Pacific.Islander.Lower.CI    0.307794210 -0.1227922039 -0.0030298320
## Asian.or.Pacific.Islander.Upper.CI    0.036520205 -0.0240434247 -0.0074297123
## Year_Factor                          -0.014153980 -0.0006141133  0.0031035281
##                                              PC19          PC20          PC21
## Denominator                          -0.005210990 -0.0108815509 -0.0018599525
## Prevalence                           -0.285302758  0.0565503131 -0.0554442791
## Lower.CI                             -0.143515899 -0.3784729134  0.0963033227
## Upper.CI                             -0.171409727  0.1902010510  0.1119305422
## Year                                 -0.005177823 -0.0020095025 -0.0017372689
## Numerator_ASD                        -0.003467409  0.0404947970  0.0001958521
## Numerator_NonASD                     -0.005214302 -0.0116720362 -0.0018846648
## Proportion                           -0.302090055  0.0151115592 -0.0702821400
## Chi_Wilson_Corrected_Lower.CI        -0.278340931 -0.2206083359 -0.1431343985
## Chi_Wilson_Corrected_Upper.CI        -0.304222652  0.2443881706  0.0890220052
## Male.Prevalence                       0.414293955  0.0239820550 -0.0348505823
## Male.Lower.CI                         0.440018597 -0.2379887985 -0.1511241285
## Male.Upper.CI                         0.413687330  0.2990904890  0.1703077607
## Female.Prevalence                     0.025038762  0.4682950129  0.1534034908
## Female.Lower.CI                       0.124628203  0.0063894551 -0.0015093935
## Female.Upper.CI                       0.109518412 -0.4807298304 -0.1663831931
## Non.hispanic.white.Prevalence         0.010597860  0.2526392418 -0.7349388945
## Non.hispanic.white.Lower.CI           0.046295962 -0.1020037859  0.4503852348
## Non.hispanic.white.Upper.CI          -0.062344252 -0.1665754799  0.2900841766
## Non.hispanic.black.Prevalence         0.134611430  0.0672056936  0.0528530356
## Non.hispanic.black.Lower.CI          -0.099449469 -0.0326245865 -0.0313159777
## Non.hispanic.black.Upper.CI          -0.046660090 -0.0279877419 -0.0231751879
## Hispanic.Prevalence                   0.012294019 -0.0240840261 -0.0528641359
## Hispanic.Lower.CI                     0.005507740  0.0225525842  0.0393534351
## Hispanic.Upper.CI                    -0.016888532  0.0007034261  0.0196242415
## Asian.or.Pacific.Islander.Prevalence -0.058239647 -0.0141023748 -0.0233453712
## Asian.or.Pacific.Islander.Lower.CI    0.049175454  0.0108029101  0.0275391054
## Asian.or.Pacific.Islander.Upper.CI    0.008213596  0.0006663769 -0.0028498942
## Year_Factor                          -0.005177823 -0.0020095025 -0.0017372689
##                                               PC22          PC23          PC24
## Denominator                          -0.0031013695 -0.0031894096 -0.0014631950
## Prevalence                            0.0756718370  0.0238379410  0.0868886501
## Lower.CI                             -0.7085068043  0.0283496139 -0.3308827587
## Upper.CI                             -0.2971399458 -0.4829275882  0.5851375352
## Year                                 -0.0006307751 -0.0006855255  0.0019947827
## Numerator_ASD                         0.0011242656  0.0097845971  0.0050281365
## Numerator_NonASD                     -0.0031556699 -0.0033868856 -0.0015626428
## Proportion                            0.2333063497  0.1243505388 -0.0670591987
## Chi_Wilson_Corrected_Lower.CI         0.2709516005 -0.0091512095  0.1788590033
## Chi_Wilson_Corrected_Upper.CI         0.2325309304  0.2118122496 -0.4179633897
## Male.Prevalence                      -0.0817794385  0.6855761849  0.4207686247
## Male.Lower.CI                         0.3727036119 -0.4588619635 -0.0995932337
## Male.Upper.CI                        -0.1240987320 -0.1431780117 -0.3625898343
## Female.Prevalence                     0.0024129085 -0.0326853957  0.0153936806
## Female.Lower.CI                      -0.0089647050  0.0201187942 -0.0300265298
## Female.Upper.CI                       0.0398806865  0.0282325487  0.0054628558
## Non.hispanic.white.Prevalence        -0.1953050732 -0.0270939554 -0.0771653284
## Non.hispanic.white.Lower.CI           0.1027132221  0.0256704531  0.0526516368
## Non.hispanic.white.Upper.CI           0.0901079842 -0.0052494621  0.0277673333
## Non.hispanic.black.Prevalence         0.0284981252 -0.0049101012  0.0071736054
## Non.hispanic.black.Lower.CI          -0.0145964275  0.0066677520 -0.0037465768
## Non.hispanic.black.Upper.CI          -0.0123058623  0.0024684427 -0.0026523716
## Hispanic.Prevalence                  -0.0289055583 -0.0039940672  0.0035008529
## Hispanic.Lower.CI                     0.0199660515  0.0051560484 -0.0045566363
## Hispanic.Upper.CI                     0.0051984952 -0.0002646355  0.0016253686
## Asian.or.Pacific.Islander.Prevalence -0.0092221888 -0.0004590034 -0.0075629453
## Asian.or.Pacific.Islander.Lower.CI    0.0071632536  0.0012340965  0.0096963072
## Asian.or.Pacific.Islander.Upper.CI    0.0003323829  0.0008386062 -0.0006132191
## Year_Factor                          -0.0006307751 -0.0006855255  0.0019947827
##                                               PC25          PC26          PC27
## Denominator                          -0.0019773931 -0.0009302308 -0.0013536379
## Prevalence                            0.7831234326 -0.3671668064 -0.2162862949
## Lower.CI                             -0.0820428759 -0.0672427682  0.0031243708
## Upper.CI                             -0.2414724533 -0.0708926328  0.0256060469
## Year                                 -0.0012938168 -0.0002463292 -0.0003758126
## Numerator_ASD                         0.0087121064  0.0013818588  0.0051832098
## Numerator_NonASD                     -0.0021432557 -0.0009636654 -0.0014543649
## Proportion                           -0.0136048222  0.0416186791  0.8498478261
## Chi_Wilson_Corrected_Lower.CI        -0.0503556273  0.6815274907 -0.3277908891
## Chi_Wilson_Corrected_Upper.CI        -0.4393746983 -0.2439512003 -0.3457423044
## Male.Prevalence                      -0.1030151094 -0.0872020368 -0.0265721430
## Male.Lower.CI                        -0.1515751950 -0.3377241531 -0.0122676734
## Male.Upper.CI                         0.2926662743  0.4555209175  0.0444496253
## Female.Prevalence                    -0.0372722476  0.0014565319 -0.0020896067
## Female.Lower.CI                      -0.0043649909 -0.0050147255  0.0015469139
## Female.Upper.CI                       0.0486591913  0.0027110286  0.0027119996
## Non.hispanic.white.Prevalence        -0.0416989891  0.0120481563 -0.0166378433
## Non.hispanic.white.Lower.CI           0.0281117435 -0.0190080934  0.0113449683
## Non.hispanic.white.Upper.CI           0.0083233916  0.0058665081  0.0039425441
## Non.hispanic.black.Prevalence         0.0115510294 -0.0005495292  0.0027018177
## Non.hispanic.black.Lower.CI          -0.0065249565  0.0027747580 -0.0015639929
## Non.hispanic.black.Upper.CI          -0.0040211558 -0.0001046730 -0.0013412565
## Hispanic.Prevalence                  -0.0008345422 -0.0093453692  0.0001829209
## Hispanic.Lower.CI                     0.0014899411  0.0072452759  0.0007042399
## Hispanic.Upper.CI                    -0.0021969682  0.0017161698 -0.0011465871
## Asian.or.Pacific.Islander.Prevalence -0.0018575781  0.0024664369 -0.0027322785
## Asian.or.Pacific.Islander.Lower.CI    0.0007353339 -0.0044544917  0.0030624619
## Asian.or.Pacific.Islander.Upper.CI    0.0003174803  0.0001204326  0.0001239471
## Year_Factor                          -0.0012938168 -0.0002463292 -0.0003758126
##                                               PC28          PC29
## Denominator                          -7.111106e-01  0.000000e+00
## Prevalence                           -1.005307e-13 -2.208448e-14
## Lower.CI                              2.962908e-15  4.557548e-15
## Upper.CI                             -2.391143e-14  1.063775e-15
## Year                                 -1.283695e-16 -7.071068e-01
## Numerator_ASD                         1.153940e-02 -1.054069e-17
## Numerator_NonASD                      7.029855e-01  5.333559e-17
## Proportion                            2.211356e-13  6.430623e-14
## Chi_Wilson_Corrected_Lower.CI        -7.423402e-14 -3.316080e-14
## Chi_Wilson_Corrected_Upper.CI        -3.841372e-14 -1.831348e-14
## Male.Prevalence                      -1.956768e-14 -1.231453e-15
## Male.Lower.CI                         8.590351e-15  1.770676e-15
## Male.Upper.CI                         2.232242e-14  2.333698e-15
## Female.Prevalence                    -7.632783e-16  7.782343e-16
## Female.Lower.CI                       5.034168e-15  7.696403e-16
## Female.Upper.CI                      -1.595946e-15 -8.188413e-16
## Non.hispanic.white.Prevalence         2.968112e-15  4.025007e-16
## Non.hispanic.white.Lower.CI          -1.882175e-15  1.238049e-15
## Non.hispanic.white.Upper.CI          -1.894318e-15 -1.664700e-15
## Non.hispanic.black.Prevalence         1.703498e-15  3.293477e-16
## Non.hispanic.black.Lower.CI          -1.450229e-15 -2.933425e-16
## Non.hispanic.black.Upper.CI          -6.106227e-16 -2.291584e-16
## Hispanic.Prevalence                  -5.342948e-16  6.235171e-16
## Hispanic.Lower.CI                     9.992007e-16 -1.641974e-16
## Hispanic.Upper.CI                    -1.665335e-16 -4.494615e-16
## Asian.or.Pacific.Islander.Prevalence -1.040834e-15 -7.760380e-16
## Asian.or.Pacific.Islander.Lower.CI    4.163336e-16  7.598798e-16
## Asian.or.Pacific.Islander.Upper.CI    7.355228e-16  2.606312e-16
## Year_Factor                          -8.673617e-17  7.071068e-01
# Summarise the importance of the components found.

summary(pc)
## Importance of components:
##                           PC1    PC2     PC3     PC4     PC5     PC6     PC7
## Standard deviation     4.6564 1.8210 1.11227 0.95454 0.74374 0.62294 0.51884
## Proportion of Variance 0.7477 0.1143 0.04266 0.03142 0.01907 0.01338 0.00928
## Cumulative Proportion  0.7477 0.8620 0.90466 0.93607 0.95515 0.96853 0.97781
##                            PC8     PC9    PC10    PC11    PC12    PC13    PC14
## Standard deviation     0.48282 0.42371 0.30975 0.22966 0.21749 0.14145 0.08282
## Proportion of Variance 0.00804 0.00619 0.00331 0.00182 0.00163 0.00069 0.00024
## Cumulative Proportion  0.98585 0.99204 0.99535 0.99717 0.99880 0.99949 0.99973
##                           PC15    PC16    PC17    PC18    PC19    PC20     PC21
## Standard deviation     0.06362 0.04164 0.02968 0.02474 0.01782 0.01467 0.009428
## Proportion of Variance 0.00014 0.00006 0.00003 0.00002 0.00001 0.00001 0.000000
## Cumulative Proportion  0.99987 0.99993 0.99996 0.99998 0.99999 1.00000 1.000000
##                            PC22     PC23     PC24     PC25     PC26      PC27
## Standard deviation     0.004768 0.003824 0.002852 0.001504 0.001409 0.0005042
## Proportion of Variance 0.000000 0.000000 0.000000 0.000000 0.000000 0.0000000
## Cumulative Proportion  1.000000 1.000000 1.000000 1.000000 1.000000 1.0000000
##                             PC28      PC29
## Standard deviation     5.196e-16 4.247e-16
## Proportion of Variance 0.000e+00 0.000e+00
## Cumulative Proportion  1.000e+00 1.000e+00
# Display a plot showing the relative importance of the components.

plot(pc, main="")
title(main="Principal Components Importance ADV_ASD_State_R.csv",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
axis(1, at=seq(0.7, ncol(pc$rotation)*1.2, 1.2), labels=colnames(pc$rotation), lty=0)

# Display a plot showing the two most principal components.

biplot(pc, main="")
title(main="Principal Components ADV_ASD_State_R.csv",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

<h3>
Rattle: EDA Explore & Test: Test
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 11:42:02 x86_64-pc-linux-gnu 

# Perform Test 

# Use the fBasics package for statistical tests.

library(fBasics, quietly=TRUE)

# Perform the test.

locationTest(na.omit(crs$dataset[, "Male.Prevalence"]), na.omit(crs$dataset[, "Female.Prevalence"]))
## 
## Title:
##  t Test
## 
## Test Results:
##   PARAMETER:
##     x Observations: 86
##     y Observations: 86
##     mu: 0
##   SAMPLE ESTIMATES:
##     Mean of x: 18.2791
##     Mean of y: 4.2477
##     Var  of x: 72.9445
##     Var  of y: 4.4698
##   STATISTIC:
##                 T: 14.789
##     T | Equal Var: 14.789
##   P VALUE:
##     Alternative Two-Sided: < 2.2e-16 
##     Alternative      Less: 1 
##     Alternative   Greater: < 2.2e-16 
##     Alternative Two-Sided | Equal Var: < 2.2e-16 
##     Alternative      Less | Equal Var: 1 
##     Alternative   Greater | Equal Var: < 2.2e-16 
##   CONFIDENCE INTERVAL:
##     Two-Sided: 12.1479, 15.9148
##          Less: -Inf, 15.6073
##       Greater: 12.4555, Inf
##     Two-Sided | Equal Var: 12.1585, 15.9043
##          Less | Equal Var: -Inf, 15.6005
##       Greater | Equal Var: 12.4623, Inf
## 
## Description:
##  Thu Feb 20 15:41:11 2020

#=======================================================================
# Rattle timestamp: 2019-12-23 11:46:39 x86_64-pc-linux-gnu 

# Perform Test 

# Use the fBasics package for statistical tests.

library(fBasics, quietly=TRUE)

# Perform the test.

locationTest(na.omit(crs$dataset[, "Prevalence"]), na.omit(crs$dataset[, "Hispanic.Prevalence"]))
## 
## Title:
##  t Test
## 
## Test Results:
##   PARAMETER:
##     x Observations: 1692
##     y Observations: 77
##     mu: 0
##   SAMPLE ESTIMATES:
##     Mean of x: 7.191
##     Mean of y: 7.8909
##     Var  of x: 34.34
##     Var  of y: 27.4158
##   STATISTIC:
##                 T: -1.1409
##     T | Equal Var: -1.0294
##   P VALUE:
##     Alternative Two-Sided: 0.2571 
##     Alternative      Less: 0.1286 
##     Alternative   Greater: 0.8714 
##     Alternative Two-Sided | Equal Var: 0.3034 
##     Alternative      Less | Equal Var: 0.1517 
##     Alternative   Greater | Equal Var: 0.8483 
##   CONFIDENCE INTERVAL:
##     Two-Sided: -1.9197, 0.5199
##          Less: -Inf, 0.3203
##       Greater: -1.7201, Inf
##     Two-Sided | Equal Var: -2.0333, 0.6335
##          Less | Equal Var: -Inf, 0.419
##       Greater | Equal Var: -1.8188, Inf
## 
## Description:
##  Thu Feb 20 15:41:11 2020

#=======================================================================
# Rattle timestamp: 2019-12-23 11:47:53 x86_64-pc-linux-gnu 

# Perform Test 

# Use the fBasics package for statistical tests.

library(fBasics, quietly=TRUE)

# Perform the test.

locationTest(na.omit(crs$dataset[crs$dataset[["Prevalence_Risk4"]] == "High", "Prevalence"]), na.omit(crs$dataset[crs$dataset[["Prevalence_Risk4"]] == "Low", "Prevalence"]))
## 
## Title:
##  t Test
## 
## Test Results:
##   PARAMETER:
##     x Observations: 294
##     y Observations: 740
##     mu: 0
##   SAMPLE ESTIMATES:
##     Mean of x: 13.4194
##     Mean of y: 2.8755
##     Var  of x: 7.6326
##     Var  of y: 1.3514
##   STATISTIC:
##                 T: 63.2522
##     T | Equal Var: 86.3832
##   P VALUE:
##     Alternative Two-Sided: < 2.2e-16 
##     Alternative      Less: 1 
##     Alternative   Greater: < 2.2e-16 
##     Alternative Two-Sided | Equal Var: < 2.2e-16 
##     Alternative      Less | Equal Var: 1 
##     Alternative   Greater | Equal Var: < 2.2e-16 
##   CONFIDENCE INTERVAL:
##     Two-Sided: 10.2159, 10.8717
##          Less: -Inf, 10.8188
##       Greater: 10.2689, Inf
##     Two-Sided | Equal Var: 10.3043, 10.7834
##          Less | Equal Var: -Inf, 10.7448
##       Greater | Equal Var: 10.3429, Inf
## 
## Description:
##  Thu Feb 20 15:41:12 2020
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Process & Transform Data

<h3>
Rattle: Process & Transform Data: Select Variables
</h3>
names(crs$dataset)
##  [1] "State"                               
##  [2] "Denominator"                         
##  [3] "Prevalence"                          
##  [4] "Lower.CI"                            
##  [5] "Upper.CI"                            
##  [6] "Year"                                
##  [7] "Source"                              
##  [8] "Source_Full1"                        
##  [9] "State_Full1"                         
## [10] "State_Full2"                         
## [11] "Numerator_ASD"                       
## [12] "Numerator_NonASD"                    
## [13] "Proportion"                          
## [14] "Chi_Wilson_Corrected_Lower.CI"       
## [15] "Chi_Wilson_Corrected_Upper.CI"       
## [16] "Male.Prevalence"                     
## [17] "Male.Lower.CI"                       
## [18] "Male.Upper.CI"                       
## [19] "Female.Prevalence"                   
## [20] "Female.Lower.CI"                     
## [21] "Female.Upper.CI"                     
## [22] "Non.hispanic.white.Prevalence"       
## [23] "Non.hispanic.white.Lower.CI"         
## [24] "Non.hispanic.white.Upper.CI"         
## [25] "Non.hispanic.black.Prevalence"       
## [26] "Non.hispanic.black.Lower.CI"         
## [27] "Non.hispanic.black.Upper.CI"         
## [28] "Hispanic.Prevalence"                 
## [29] "Hispanic.Lower.CI"                   
## [30] "Hispanic.Upper.CI"                   
## [31] "Asian.or.Pacific.Islander.Prevalence"
## [32] "Asian.or.Pacific.Islander.Lower.CI"  
## [33] "Asian.or.Pacific.Islander.Upper.CI"  
## [34] "State_Region"                        
## [35] "Source_UC"                           
## [36] "Source_Full3"                        
## [37] "Prevalence_Risk2"                    
## [38] "Prevalence_Risk4"                    
## [39] "Year_Factor"

Select variables to build classification model

Target:

  • Prevalence_Risk4

Inputs:

  • Denominator

  • Year

  • Source

  • State_Region

Note: It’s not recommended ot use State, which has more than 32 levels.

https://stats.stackexchange.com/questions/49243/rs-randomforest-can-not-handle-more-than-32-levels-what-is-workaround

#=======================================================================
# Rattle timestamp: 2019-12-23 15:06:51 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(88)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("Denominator", "Year", "Source",
                   "State_Region")

crs$numeric   <- c("Denominator", "Year")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence_Risk4"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Prevalence", "Lower.CI", "Upper.CI", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk2", "Year_Factor")
crs$weights   <- NULL

# Adjust in-line plot size to M x N
options(repr.plot.width=8, repr.plot.height=5)
#=======================================================================
# Rattle timestamp: 2019-12-23 14:59:20 x86_64-pc-linux-gnu 

# The 'gplots' package provides the 'barplot2' function.

library(gplots, quietly=TRUE)

#=======================================================================
# Rattle timestamp: 2019-12-23 14:59:20 x86_64-pc-linux-gnu 

# Bar Plot 

# Generate the summary data for plotting.

ds <- rbind(summary(na.omit(crs$dataset[crs$train,]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="High",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Low",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Medium",]$Source)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Very High",]$Source)))

# Sort the entries.

ord <- order(ds[1,], decreasing=TRUE)

# Plot the data.

bp <-  barplot2(ds[,ord], beside=TRUE, ylab="Frequency", xlab="Source", ylim=c(0, 715), col=colorspace::rainbow_hcl(5))

# Add the actual frequencies.

text(bp, ds[,ord]+24, ds[,ord])

# Add a legend to the plot.

legend("topright", bty="n", c("All","High","Low","Medium","Very High"),  fill=colorspace::rainbow_hcl(5))

# Add a title to the plot.

title(main="Distribution of Source (sample)\nby Prevalence_Risk4",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

#=======================================================================
# Rattle timestamp: 2019-12-23 14:59:21 x86_64-pc-linux-gnu 

# Bar Plot 

# Generate the summary data for plotting.

ds <- rbind(summary(na.omit(crs$dataset[crs$train,]$State_Region)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="High",]$State_Region)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Low",]$State_Region)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Medium",]$State_Region)),
    summary(na.omit(crs$dataset[crs$train,][crs$dataset[crs$train,]$Prevalence_Risk4=="Very High",]$State_Region)))

# Sort the entries.

ord <- order(ds[1,], decreasing=TRUE)

# Plot the data.

bp <-  barplot2(ds[,ord], beside=TRUE, ylab="Frequency", xlab="State_Region", ylim=c(0, 265), col=colorspace::rainbow_hcl(5))

# Add a legend to the plot.

legend("topright", bty="n", c("All","High","Low","Medium","Very High"),  fill=colorspace::rainbow_hcl(5))

# Add a title to the plot.

title(main="Distribution of State_Region (sample)\nby Prevalence_Risk4",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

#=======================================================================
# Rattle timestamp: 2019-12-23 12:14:28 x86_64-pc-linux-gnu 

# Display histogram plots for the selected variables. 

# Use ggplot2 to generate histogram plot for Denominator

# Generate the plot.

p01 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Denominator, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Denominator)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Denominator\n\nRattle 2019-Dec-23 12:14:28 iss-user") +
  ggplot2::ggtitle("Distribution of Denominator (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Use ggplot2 to generate histogram plot for Year

# Generate the plot.

p02 <- crs %>%
  with(dataset[train,]) %>%
  dplyr::mutate(Prevalence_Risk4=as.factor(Prevalence_Risk4)) %>%
  dplyr::select(Year, Prevalence_Risk4) %>%
  ggplot2::ggplot(ggplot2::aes(x=Year)) +
  ggplot2::geom_density(lty=3) +
  ggplot2::geom_density(ggplot2::aes(fill=Prevalence_Risk4, colour=Prevalence_Risk4), alpha=0.55) +
  ggplot2::xlab("Year\n\nRattle 2019-Dec-23 12:14:28 iss-user") +
  ggplot2::ggtitle("Distribution of Year (sample)\nby Prevalence_Risk4") +
  ggplot2::labs(fill="Prevalence_Risk4", y="Density")

# Display the plots.

gridExtra::grid.arrange(p01, p02)

Above shows that Denominator is skrewed, which need rescale transformation

<h3>
Rattle: Process & Transform Data: Rescale (log transformation)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 15:10:29 x86_64-pc-linux-gnu 

# Transform variables by rescaling. 

# Rescale Denominator.

crs$dataset[["R10_Denominator"]] <- crs$dataset[["Denominator"]]

# Take a log10 transform of the variable - treat -Inf as NA.

if (building)
{
  crs$dataset[["R10_Denominator"]] <-  log10(crs$dataset[["Denominator"]]) 
  crs$dataset[crs$dataset[["R10_Denominator"]] == -Inf & ! is.na(crs$dataset[["R10_Denominator"]]), "R10_Denominator"] <- NA
}

# When scoring transform using the training data parameters.

if (scoring)
{
  crs$dataset[["R10_Denominator"]] <-  log10(crs$dataset[["Denominator"]]) 
  crs$dataset[crs$dataset[["R10_Denominator"]] == -Inf & ! is.na(crs$dataset[["R10_Denominator"]]), "R10_Denominator"] <- NA
}

#=======================================================================
# Rattle timestamp: 2019-12-23 15:10:29 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# The following variable selections have been noted.

crs$input     <- c("Year", "Source", "State_Region",
                   "R10_Denominator")

crs$numeric   <- c("Year", "R10_Denominator")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence_Risk4"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Denominator", "Prevalence", "Lower.CI", "Upper.CI", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk2", "Year_Factor")
crs$weights   <- NULL
<h3>
Rattle: Process & Transform Data: Rescale (normalization)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 15:12:22 x86_64-pc-linux-gnu 

# Transform variables by rescaling. 

# The 'reshape' package provides the 'rescaler' function.

library(reshape, quietly=TRUE)

# Rescale Year.

crs$dataset[["RMD_Year"]] <- crs$dataset[["Year"]]

# Rescale by subtracting median and dividing by median abs deviation.

if (building)
{
  crs$dataset[["RMD_Year"]] <-  rescaler(crs$dataset[["Year"]], "robust")
}

# When scoring transform using the training data parameters.

if (scoring)
{
  crs$dataset[["RMD_Year"]] <- (crs$dataset[["Year"]] - 2007.000000)/5.930400
}

# Rescale R10_Denominator.

crs$dataset[["RMD_R10_Denominator"]] <- crs$dataset[["R10_Denominator"]]

# Rescale by subtracting median and dividing by median abs deviation.

if (building)
{
  crs$dataset[["RMD_R10_Denominator"]] <-  rescaler(crs$dataset[["R10_Denominator"]], "robust")
}

# When scoring transform using the training data parameters.

if (scoring)
{
  crs$dataset[["RMD_R10_Denominator"]] <- (crs$dataset[["R10_Denominator"]] - 5.548179)/0.598315
}

#=======================================================================
# Rattle timestamp: 2019-12-23 15:12:23 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# The following variable selections have been noted.

crs$input     <- c("Source", "State_Region", "RMD_Year",
                   "RMD_R10_Denominator")

crs$numeric   <- c("RMD_Year", "RMD_R10_Denominator")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence_Risk4"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Denominator", "Prevalence", "Lower.CI", "Upper.CI", "Year", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk2", "Year_Factor", "R10_Denominator")
crs$weights   <- NULL

Optionally, Cleanup variables by Delete Ignored

<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Train Model (Classification)

Multi-Class Classification: Prevalence_Risk4

crs$target
## [1] "Prevalence_Risk4"
crs$input
## [1] "Source"              "State_Region"        "RMD_Year"           
## [4] "RMD_R10_Denominator"
<h3>
Multi-Class Model: Decision Tree (DT)
</h3>

if(!require(rpart)){install.packages("rpart")}
## Loading required package: rpart
library('rpart')
#=======================================================================
# Rattle timestamp: 2019-12-23 15:16:48 x86_64-pc-linux-gnu 

# Decision Tree 

# The 'rpart' package provides the 'rpart' function.

library(rpart, quietly=TRUE)

# Reset the random number seed to obtain the same results each time.

set.seed(crv$seed)

# Build the Decision Tree model.

crs$rpart <- rpart(Prevalence_Risk4 ~ .,
    data=crs$dataset[crs$train, c(crs$input, crs$target)],
    method="class",
    parms=list(split="information"),
    control=rpart.control(usesurrogate=0, 
        maxsurrogate=0),
    model=TRUE)

# Generate a textual view of the Decision Tree model.

print(crs$rpart)
## n= 1184 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##  1) root 1184 675 Low (0.175675676 0.429898649 0.353040541 0.041385135)  
##    2) RMD_Year< 0.08431134 580 158 Low (0.034482759 0.727586207 0.234482759 0.003448276)  
##      4) RMD_R10_Denominator>=-1.378335 526 116 Low (0.026615970 0.779467681 0.190114068 0.003802281) *
##      5) RMD_R10_Denominator< -1.378335 54  18 Medium (0.111111111 0.222222222 0.666666667 0.000000000) *
##    3) RMD_Year>=0.08431134 604 322 Medium (0.311258278 0.144039735 0.466887417 0.077814570)  
##      6) RMD_R10_Denominator>=-1.349522 491 219 Medium (0.260692464 0.177189409 0.553971487 0.008146640)  
##       12) RMD_Year>=0.7588021 215 105 Medium (0.437209302 0.046511628 0.511627907 0.004651163)  
##         24) State_Region=D1 New England,D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific 123  44 High (0.642276423 0.008130081 0.341463415 0.008130081)  
##           48) RMD_Year>=1.096047 61   9 High (0.852459016 0.000000000 0.147540984 0.000000000) *
##           49) RMD_Year< 1.096047 62  29 Medium (0.435483871 0.016129032 0.532258065 0.016129032)  
##             98) State_Region=D1 New England 11   2 High (0.818181818 0.000000000 0.090909091 0.090909091) *
##             99) State_Region=D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific 51  19 Medium (0.352941176 0.019607843 0.627450980 0.000000000) *
##         25) State_Region=D4 West North Central,D6 East South Central,D7 West South Central,D8 Mountain 92  24 Medium (0.163043478 0.097826087 0.739130435 0.000000000) *
##       13) RMD_Year< 0.7588021 276 114 Medium (0.123188406 0.278985507 0.586956522 0.010869565) *
##      7) RMD_R10_Denominator< -1.349522 113  53 High (0.530973451 0.000000000 0.088495575 0.380530973)  
##       14) RMD_Year< 1.348982 87  31 High (0.643678161 0.000000000 0.114942529 0.241379310) *
##       15) RMD_Year>=1.348982 26   4 Very High (0.153846154 0.000000000 0.000000000 0.846153846) *
printcp(crs$rpart)
## 
## Classification tree:
## rpart(formula = Prevalence_Risk4 ~ ., data = crs$dataset[crs$train, 
##     c(crs$input, crs$target)], method = "class", model = TRUE, 
##     parms = list(split = "information"), control = rpart.control(usesurrogate = 0, 
##         maxsurrogate = 0))
## 
## Variables actually used in tree construction:
## [1] RMD_R10_Denominator RMD_Year            State_Region       
## 
## Root node error: 675/1184 = 0.5701
## 
## n= 1184 
## 
##         CP nsplit rel error  xerror     xstd
## 1 0.288889      0   1.00000 1.00000 0.025237
## 2 0.074074      1   0.71111 0.71111 0.025028
## 3 0.035556      2   0.63704 0.63852 0.024528
## 4 0.027407      3   0.60148 0.62519 0.024415
## 5 0.026667      5   0.54667 0.62667 0.024428
## 6 0.010370      6   0.52000 0.58519 0.024036
## 7 0.010000      8   0.49926 0.55852 0.023748
cat("\n")
# Time taken: 0.05 secs

# List the rules from the tree using a Rattle support function.

asRules(crs$rpart)
## 
##  Rule number: 15 [Prevalence_Risk4=Very High cover=26 (2%) prob=22.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator< -1.35
##    RMD_Year>=1.349
## 
##  Rule number: 14 [Prevalence_Risk4=High cover=87 (7%) prob=21.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator< -1.35
##    RMD_Year< 1.349
## 
##  Rule number: 13 [Prevalence_Risk4=Medium cover=276 (23%) prob=3.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year< 0.7588
## 
##  Rule number: 4 [Prevalence_Risk4=Low cover=526 (44%) prob=2.00]
##    RMD_Year< 0.08431
##    RMD_R10_Denominator>=-1.378
## 
##  Rule number: 98 [Prevalence_Risk4=High cover=11 (1%) prob=1.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D1 New England,D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific
##    RMD_Year< 1.096
##    State_Region=D1 New England
## 
##  Rule number: 25 [Prevalence_Risk4=Medium cover=92 (8%) prob=0.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D4 West North Central,D6 East South Central,D7 West South Central,D8 Mountain
## 
##  Rule number: 99 [Prevalence_Risk4=Medium cover=51 (4%) prob=0.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D1 New England,D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific
##    RMD_Year< 1.096
##    State_Region=D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific
## 
##  Rule number: 48 [Prevalence_Risk4=High cover=61 (5%) prob=0.00]
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D1 New England,D2 Middle Atlantic,D3 East North Central,D5 South Atlantic,D9 Pacific
##    RMD_Year>=1.096
## 
##  Rule number: 5 [Prevalence_Risk4=Medium cover=54 (5%) prob=0.00]
##    RMD_Year< 0.08431
##    RMD_R10_Denominator< -1.378
# Adjust in-line plot size to M x N
options(repr.plot.width=8, repr.plot.height=6)
rpart.plot::prp(crs$rpart,
    type = 2, extra = "auto", nn = TRUE,
    under = FALSE, fallen.leaves = TRUE,
    digits = 2, varlen = 0, faclen = 0, 
#    roundint = TRUE,
    cex = NULL, tweak = 1,
#    clip.facs = FALSE, 
    clip.right.labs = TRUE,
    snip = FALSE,
    box.palette = "auto", shadow.col = 0)

<h3>
Multi-Class Model: Random Forest (RF)
</h3>

if(!require(randomForest)){install.packages("randomForest")}
## Loading required package: randomForest
## randomForest 4.6-14
## Type rfNews() to see new features/changes/bug fixes.
## 
## Attaching package: 'randomForest'
## The following object is masked from 'package:timeSeries':
## 
##     outlier
## The following object is masked from 'package:ggplot2':
## 
##     margin
## The following object is masked from 'package:rattle':
## 
##     importance
library('randomForest')
#=======================================================================
# Rattle timestamp: 2019-12-23 15:40:42 x86_64-pc-linux-gnu 

# Build a Random Forest model using the traditional approach.

set.seed(crv$seed)

crs$rf <- randomForest::randomForest(Prevalence_Risk4 ~ .,
  data=crs$dataset[crs$train, c(crs$input, crs$target)], 
  ntree=500,
  mtry=2,
  importance=TRUE,
  na.action=randomForest::na.roughfix,
  replace=FALSE)

# Generate textual output of the 'Random Forest' model.

crs$rf
## 
## Call:
##  randomForest(formula = Prevalence_Risk4 ~ ., data = crs$dataset[crs$train,      c(crs$input, crs$target)], ntree = 500, mtry = 2, importance = TRUE,      replace = FALSE, na.action = randomForest::na.roughfix) 
##                Type of random forest: classification
##                      Number of trees: 500
## No. of variables tried at each split: 2
## 
##         OOB estimate of  error rate: 22.64%
## Confusion matrix:
##           High Low Medium Very High class.error
## High       138   4     55        11   0.3365385
## Low          3 443     60         3   0.1296660
## Medium      40  70    306         2   0.2679426
## Very High   14   4      2        29   0.4081633
# List the importance of the variables.

rn <- round(randomForest::importance(crs$rf), 2)
rn[order(rn[,3], decreasing=TRUE),]
##                      High    Low Medium Very High MeanDecreaseAccuracy
## RMD_Year            85.07 151.93 103.16     40.59               188.83
## State_Region        56.22  49.25  54.81      3.18                84.47
## RMD_R10_Denominator 26.47  41.32  50.31     43.59                62.56
## Source              28.10  27.31  48.10     21.90                47.57
##                     MeanDecreaseGini
## RMD_Year                      164.85
## State_Region                   81.96
## RMD_R10_Denominator           162.78
## Source                         41.03
# Time taken: 2.00 secs

#=======================================================================
# Rattle timestamp: 2019-12-23 15:40:45 x86_64-pc-linux-gnu 

# Plot the relative importance of the variables.

p <- ggVarImp(crs$rf,
              title="Variable Importance Random Forest ADV_ASD_State_R.csv")
p

# Plot the error rate against the number of trees.

plot(crs$rf, main="")
legend("topright", c("OOB", "High", "Low", "Medium", "Very High"), text.col=1:6, lty=1:3, col=1:3)
title(main="Error Rates Random Forest ADV_ASD_State_R.csv",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

if(!require(verification)){install.packages("verification")}
## Loading required package: verification
## Loading required package: fields
## Loading required package: spam
## Loading required package: dotCall64
## Loading required package: grid
## Spam version 2.5-0 (2019-12-06) is loaded.
## Type 'help( Spam)' or 'demo( spam)' for a short introduction 
## and overview of this package.
## Help for individual functions is also obtained by adding the
## suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
## 
## Attaching package: 'spam'
## The following objects are masked from 'package:base':
## 
##     backsolve, forwardsolve
## Loading required package: maps
## See https://github.com/NCAR/Fields for
##  an extensive vignette, other supplements and source code
## 
## Attaching package: 'fields'
## The following object is masked from 'package:Hmisc':
## 
##     describe
## Loading required package: boot
## 
## Attaching package: 'boot'
## The following object is masked from 'package:survival':
## 
##     aml
## The following object is masked from 'package:lattice':
## 
##     melanoma
## Loading required package: CircStats
## Loading required package: MASS
## Loading required package: dtw
## Loading required package: proxy
## 
## Attaching package: 'proxy'
## The following object is masked from 'package:spam':
## 
##     as.matrix
## The following object is masked from 'package:timeSeries':
## 
##     as.matrix
## The following objects are masked from 'package:stats':
## 
##     as.dist, dist
## The following object is masked from 'package:base':
## 
##     as.matrix
## Loaded dtw v1.21-3. See ?dtw for help, citation("dtw") for use in publication.
library('verification')
head(crs$rf$votes)
##            High        Low     Medium Very High
## 279  0.00000000 0.98870056 0.01129944 0.0000000
## 589  0.32820513 0.26153846 0.41025641 0.0000000
## 1462 0.24309392 0.00000000 0.75690608 0.0000000
## 743  0.02824859 0.67231638 0.29943503 0.0000000
## 1427 0.62637363 0.02197802 0.35164835 0.0000000
## 81   0.57627119 0.00000000 0.11299435 0.3107345
# Display tree number 1 to 3.

printRandomForests(crs$rf, 1:3)
## Random Forest Model 1 
## 
## -------------------------------------------------------------
## Tree 1 Rule 1 Node 16 Decision Very High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year <= 0.505868069607446
## 3: State_Region IN ("D3 East North Central")
## 4: RMD_R10_Denominator <= -3.93592015489017
## -----------------------------------------------------------------
## Tree 1 Rule 2 Node 17 Decision High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year <= 0.505868069607446
## 3: State_Region IN ("D3 East North Central")
## 4: RMD_R10_Denominator > -3.93592015489017
## -----------------------------------------------------------------
## Tree 1 Rule 3 Node 9 Decision High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year <= 0.505868069607446
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 4 Node 18 Decision Very High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.90481668103234
## 4: RMD_Year <= 1.18035882908404
## -----------------------------------------------------------------
## Tree 1 Rule 5 Node 28 Decision Very High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.90481668103234
## 4: RMD_Year > 1.18035882908404
## 5: RMD_R10_Denominator <= -4.06018541424385
## -----------------------------------------------------------------
## Tree 1 Rule 6 Node 46 Decision High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.90481668103234
## 4: RMD_Year > 1.18035882908404
## 5: RMD_R10_Denominator > -4.06018541424385
## 6: RMD_R10_Denominator <= -4.04649977922423
## -----------------------------------------------------------------
## Tree 1 Rule 7 Node 72 Decision High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.90481668103234
## 4: RMD_Year > 1.18035882908404
## 5: RMD_R10_Denominator > -4.06018541424385
## 6: RMD_R10_Denominator > -4.04649977922423
## 7: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 1 Rule 8 Node 73 Decision Very High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.90481668103234
## 4: RMD_Year > 1.18035882908404
## 5: RMD_R10_Denominator > -4.06018541424385
## 6: RMD_R10_Denominator > -4.04649977922423
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 9 Node 11 Decision High
##  
## 1: RMD_R10_Denominator <= -3.86457272986912
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.90481668103234
## -----------------------------------------------------------------
## Tree 1 Rule 10 Node 208 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("medi", "nsch")
## 7: RMD_R10_Denominator <= -1.22258237140411
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 11 Node 209 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("medi", "nsch")
## 7: RMD_R10_Denominator <= -1.22258237140411
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_Year > -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 12 Node 153 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("medi", "nsch")
## 7: RMD_R10_Denominator <= -1.22258237140411
## 8: Source IN ("medi")
## 9: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 13 Node 107 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("medi", "nsch")
## 7: RMD_R10_Denominator <= -1.22258237140411
## 8: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 14 Node 75 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("medi", "nsch")
## 7: RMD_R10_Denominator > -1.22258237140411
## -----------------------------------------------------------------
## Tree 1 Rule 15 Node 49 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= -0.783095360058372
## 6: Source IN ("addm", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 16 Node 50 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > -0.783095360058372
## 6: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 17 Node 76 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > -0.783095360058372
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 18 Node 154 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > -0.783095360058372
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.421556724672872
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator <= 0.109948689774744
## -----------------------------------------------------------------
## Tree 1 Rule 19 Node 155 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > -0.783095360058372
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.421556724672872
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator > 0.109948689774744
## -----------------------------------------------------------------
## Tree 1 Rule 20 Node 109 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > -0.783095360058372
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.421556724672872
## 8: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 21 Node 156 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 22 Node 157 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 23 Node 158 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year > 0.421556724672872
## 9: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 24 Node 262 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year > 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_Year <= 0.590179414542021
## 11: RMD_R10_Denominator <= -0.508863201282255
## -----------------------------------------------------------------
## Tree 1 Rule 25 Node 263 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year > 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_Year <= 0.590179414542021
## 11: RMD_R10_Denominator > -0.508863201282255
## -----------------------------------------------------------------
## Tree 1 Rule 26 Node 264 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year > 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_Year > 0.590179414542021
## 11: RMD_R10_Denominator <= -0.907846444100072
## -----------------------------------------------------------------
## Tree 1 Rule 27 Node 265 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year <= 0.75880210441117
## 8: RMD_Year > 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_Year > 0.590179414542021
## 11: RMD_R10_Denominator > -0.907846444100072
## -----------------------------------------------------------------
## Tree 1 Rule 28 Node 112 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 29 Node 113 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator <= -0.0986104269827017
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 30 Node 53 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year <= 0.927424794280318
## 6: RMD_R10_Denominator > -0.0986104269827017
## -----------------------------------------------------------------
## Tree 1 Rule 31 Node 33 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.252934034803723
## 5: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 32 Node 34 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator <= -1.46102868589955
## -----------------------------------------------------------------
## Tree 1 Rule 33 Node 308 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year <= -0.927424794280318
## 11: RMD_Year <= -1.09604748414947
## 12: RMD_R10_Denominator <= -0.00746028123080034
## -----------------------------------------------------------------
## Tree 1 Rule 34 Node 309 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year <= -0.927424794280318
## 11: RMD_Year <= -1.09604748414947
## 12: RMD_R10_Denominator > -0.00746028123080034
## -----------------------------------------------------------------
## Tree 1 Rule 35 Node 310 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year <= -0.927424794280318
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator <= 0.0947593676182268
## -----------------------------------------------------------------
## Tree 1 Rule 36 Node 311 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year <= -0.927424794280318
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.0947593676182268
## -----------------------------------------------------------------
## Tree 1 Rule 37 Node 268 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year > -0.927424794280318
## 11: RMD_R10_Denominator <= -0.0677701099358654
## -----------------------------------------------------------------
## Tree 1 Rule 38 Node 269 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year <= -0.75880210441117
## 10: RMD_Year > -0.927424794280318
## 11: RMD_R10_Denominator > -0.0677701099358654
## -----------------------------------------------------------------
## Tree 1 Rule 39 Node 161 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator <= 0.543072616265019
## 9: RMD_Year > -0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 40 Node 115 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central")
## 8: RMD_R10_Denominator > 0.543072616265019
## -----------------------------------------------------------------
## Tree 1 Rule 41 Node 81 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 42 Node 82 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator <= 0.573495453216132
## -----------------------------------------------------------------
## Tree 1 Rule 43 Node 116 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.573495453216132
## 8: RMD_R10_Denominator <= 0.577633017192642
## -----------------------------------------------------------------
## Tree 1 Rule 44 Node 214 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.573495453216132
## 8: RMD_R10_Denominator > 0.577633017192642
## 9: State_Region IN ("D3 East North Central")
## 10: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 45 Node 215 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.573495453216132
## 8: RMD_R10_Denominator > 0.577633017192642
## 9: State_Region IN ("D3 East North Central")
## 10: RMD_Year > -0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 46 Node 163 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= -0.252934034803723
## 5: RMD_R10_Denominator > -1.46102868589955
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.573495453216132
## 8: RMD_R10_Denominator > 0.577633017192642
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 47 Node 84 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator <= -1.37459331517596
## 7: RMD_Year <= 0
## -----------------------------------------------------------------
## Tree 1 Rule 48 Node 85 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator <= -1.37459331517596
## 7: RMD_Year > 0
## -----------------------------------------------------------------
## Tree 1 Rule 49 Node 164 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: RMD_Year <= 0.505868069607446
## 9: RMD_R10_Denominator <= -1.32399479801174
## -----------------------------------------------------------------
## Tree 1 Rule 50 Node 165 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: RMD_Year <= 0.505868069607446
## 9: RMD_R10_Denominator > -1.32399479801174
## -----------------------------------------------------------------
## Tree 1 Rule 51 Node 119 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: RMD_Year > 0.505868069607446
## -----------------------------------------------------------------
## Tree 1 Rule 52 Node 394 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator <= -0.163312101429127
## 14: Source IN ("medi")
## 15: RMD_R10_Denominator <= -0.663833511295947
## -----------------------------------------------------------------
## Tree 1 Rule 53 Node 395 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator <= -0.163312101429127
## 14: Source IN ("medi")
## 15: RMD_R10_Denominator > -0.663833511295947
## -----------------------------------------------------------------
## Tree 1 Rule 54 Node 404 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator <= -0.163312101429127
## 14: Source IN ("addm", "nsch", "sped")
## 15: RMD_Year <= 0.0843113449345744
## 16: RMD_R10_Denominator <= -0.540210992664561
## -----------------------------------------------------------------
## Tree 1 Rule 55 Node 405 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator <= -0.163312101429127
## 14: Source IN ("addm", "nsch", "sped")
## 15: RMD_Year <= 0.0843113449345744
## 16: RMD_R10_Denominator > -0.540210992664561
## -----------------------------------------------------------------
## Tree 1 Rule 56 Node 397 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator <= -0.163312101429127
## 14: Source IN ("addm", "nsch", "sped")
## 15: RMD_Year > 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 57 Node 347 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year <= 0.252934034803723
## 13: RMD_R10_Denominator > -0.163312101429127
## -----------------------------------------------------------------
## Tree 1 Rule 58 Node 313 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year <= 0.590179414542021
## 12: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 59 Node 398 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year > 0.590179414542021
## 12: RMD_R10_Denominator <= 0.174535140506537
## 13: Source IN ("medi")
## 14: RMD_R10_Denominator <= -0.250951045318659
## 15: RMD_R10_Denominator <= -0.871060565143893
## -----------------------------------------------------------------
## Tree 1 Rule 60 Node 399 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year > 0.590179414542021
## 12: RMD_R10_Denominator <= 0.174535140506537
## 13: Source IN ("medi")
## 14: RMD_R10_Denominator <= -0.250951045318659
## 15: RMD_R10_Denominator > -0.871060565143893
## -----------------------------------------------------------------
## Tree 1 Rule 61 Node 379 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year > 0.590179414542021
## 12: RMD_R10_Denominator <= 0.174535140506537
## 13: Source IN ("medi")
## 14: RMD_R10_Denominator > -0.250951045318659
## -----------------------------------------------------------------
## Tree 1 Rule 62 Node 349 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year > 0.590179414542021
## 12: RMD_R10_Denominator <= 0.174535140506537
## 13: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 63 Node 315 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.426894396375776
## 11: RMD_Year > 0.590179414542021
## 12: RMD_R10_Denominator > 0.174535140506537
## -----------------------------------------------------------------
## Tree 1 Rule 64 Node 400 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("medi")
## 14: State_Region IN ("D3 East North Central")
## 15: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 65 Node 401 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("medi")
## 14: State_Region IN ("D3 East North Central")
## 15: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 66 Node 381 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("medi")
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 67 Node 382 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("addm", "nsch", "sped")
## 14: State_Region IN ("D3 East North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 68 Node 402 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("addm", "nsch", "sped")
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 15: RMD_R10_Denominator <= 0.698228553636196
## -----------------------------------------------------------------
## Tree 1 Rule 69 Node 403 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator <= 0.831862381168912
## 13: Source IN ("addm", "nsch", "sped")
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 15: RMD_R10_Denominator > 0.698228553636196
## -----------------------------------------------------------------
## Tree 1 Rule 70 Node 317 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year <= 0.252934034803723
## 12: RMD_R10_Denominator > 0.831862381168912
## -----------------------------------------------------------------
## Tree 1 Rule 71 Node 318 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year > 0.252934034803723
## 12: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 72 Node 384 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year > 0.252934034803723
## 12: Source IN ("addm", "nsch", "sped")
## 13: State_Region IN ("D5 South Atlantic")
## 14: RMD_R10_Denominator <= 0.438363454729749
## -----------------------------------------------------------------
## Tree 1 Rule 73 Node 385 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year > 0.252934034803723
## 12: Source IN ("addm", "nsch", "sped")
## 13: State_Region IN ("D5 South Atlantic")
## 14: RMD_R10_Denominator > 0.438363454729749
## -----------------------------------------------------------------
## Tree 1 Rule 74 Node 386 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year > 0.252934034803723
## 12: Source IN ("addm", "nsch", "sped")
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.640147814635059
## -----------------------------------------------------------------
## Tree 1 Rule 75 Node 387 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.426894396375776
## 11: RMD_Year > 0.252934034803723
## 12: Source IN ("addm", "nsch", "sped")
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.640147814635059
## -----------------------------------------------------------------
## Tree 1 Rule 76 Node 274 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator <= 0.499338774817655
## 11: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 77 Node 275 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator <= 0.499338774817655
## 11: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 78 Node 320 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator > 0.499338774817655
## 11: Source IN ("medi")
## 12: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 1 Rule 79 Node 321 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator > 0.499338774817655
## 11: Source IN ("medi")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 80 Node 277 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator <= 0.879845410106153
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator > 0.499338774817655
## 11: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 81 Node 220 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator > 0.879845410106153
## 9: RMD_Year <= 0.252934034803723
## 10: RMD_R10_Denominator <= 1.30216088006918
## -----------------------------------------------------------------
## Tree 1 Rule 82 Node 221 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator > 0.879845410106153
## 9: RMD_Year <= 0.252934034803723
## 10: RMD_R10_Denominator > 1.30216088006918
## -----------------------------------------------------------------
## Tree 1 Rule 83 Node 169 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year <= 1.09604748414947
## 6: RMD_R10_Denominator > -1.37459331517596
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_R10_Denominator > 0.879845410106153
## 9: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 84 Node 88 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("addm")
## 7: State_Region IN ("D3 East North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 85 Node 122 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("addm")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= -2.18707454857142
## -----------------------------------------------------------------
## Tree 1 Rule 86 Node 123 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("addm")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator > -2.18707454857142
## -----------------------------------------------------------------
## Tree 1 Rule 87 Node 90 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("medi", "nsch", "sped")
## 7: RMD_R10_Denominator <= 1.08010596289803
## -----------------------------------------------------------------
## Tree 1 Rule 88 Node 170 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("medi", "nsch", "sped")
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_Year <= 1.26467017401862
## 9: RMD_R10_Denominator <= 1.30635895630439
## -----------------------------------------------------------------
## Tree 1 Rule 89 Node 171 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("medi", "nsch", "sped")
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_Year <= 1.26467017401862
## 9: RMD_R10_Denominator > 1.30635895630439
## -----------------------------------------------------------------
## Tree 1 Rule 90 Node 125 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic")
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > -0.252934034803723
## 5: RMD_Year > 1.09604748414947
## 6: Source IN ("medi", "nsch", "sped")
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_Year > 1.26467017401862
## -----------------------------------------------------------------
## Tree 1 Rule 91 Node 60 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator <= -1.97242428357668
## 5: State_Region IN ("D6 East South Central")
## 6: RMD_R10_Denominator <= -2.2479394041529
## -----------------------------------------------------------------
## Tree 1 Rule 92 Node 61 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator <= -1.97242428357668
## 5: State_Region IN ("D6 East South Central")
## 6: RMD_R10_Denominator > -2.2479394041529
## -----------------------------------------------------------------
## Tree 1 Rule 93 Node 39 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator <= -1.97242428357668
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 94 Node 40 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator > -1.97242428357668
## 5: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 1 Rule 95 Node 62 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator > -1.97242428357668
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= -0.505868069607446
## -----------------------------------------------------------------
## Tree 1 Rule 96 Node 63 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("addm", "nsch")
## 4: RMD_R10_Denominator > -1.97242428357668
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > -0.505868069607446
## -----------------------------------------------------------------
## Tree 1 Rule 97 Node 172 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year <= -0.75880210441117
## 9: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 98 Node 222 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year <= -0.75880210441117
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.155191893235663
## -----------------------------------------------------------------
## Tree 1 Rule 99 Node 223 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year <= -0.75880210441117
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.155191893235663
## -----------------------------------------------------------------
## Tree 1 Rule 100 Node 224 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator <= 0.0368516951853818
## 10: RMD_R10_Denominator <= -0.0501599158601311
## -----------------------------------------------------------------
## Tree 1 Rule 101 Node 225 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator <= 0.0368516951853818
## 10: RMD_R10_Denominator > -0.0501599158601311
## -----------------------------------------------------------------
## Tree 1 Rule 102 Node 175 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator > 0.0368516951853818
## -----------------------------------------------------------------
## Tree 1 Rule 103 Node 128 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year > -0.252934034803723
## 8: RMD_R10_Denominator <= -0.053184784167524
## -----------------------------------------------------------------
## Tree 1 Rule 104 Node 129 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year > -0.252934034803723
## 8: RMD_R10_Denominator > -0.053184784167524
## -----------------------------------------------------------------
## Tree 1 Rule 105 Node 226 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= 0.202311752463542
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= -0.0622913718394808
## 10: RMD_R10_Denominator <= -0.145491019957967
## -----------------------------------------------------------------
## Tree 1 Rule 106 Node 227 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= 0.202311752463542
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= -0.0622913718394808
## 10: RMD_R10_Denominator > -0.145491019957967
## -----------------------------------------------------------------
## Tree 1 Rule 107 Node 228 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= 0.202311752463542
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator > -0.0622913718394808
## 10: RMD_R10_Denominator <= 0.042272045460116
## -----------------------------------------------------------------
## Tree 1 Rule 108 Node 229 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= 0.202311752463542
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator > -0.0622913718394808
## 10: RMD_R10_Denominator > 0.042272045460116
## -----------------------------------------------------------------
## Tree 1 Rule 109 Node 131 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= 0.202311752463542
## 8: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 110 Node 132 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > 0.202311752463542
## 8: RMD_R10_Denominator <= 1.22612708403867
## -----------------------------------------------------------------
## Tree 1 Rule 111 Node 133 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year <= 0.421556724672872
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > 0.202311752463542
## 8: RMD_R10_Denominator > 1.22612708403867
## -----------------------------------------------------------------
## Tree 1 Rule 112 Node 178 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: State_Region IN ("D6 East South Central")
## 9: RMD_R10_Denominator <= -0.0217929261255351
## -----------------------------------------------------------------
## Tree 1 Rule 113 Node 179 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: State_Region IN ("D6 East South Central")
## 9: RMD_R10_Denominator > -0.0217929261255351
## -----------------------------------------------------------------
## Tree 1 Rule 114 Node 135 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 115 Node 180 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator <= 0.252513856822223
## 9: RMD_R10_Denominator <= 0.156944484759585
## -----------------------------------------------------------------
## Tree 1 Rule 116 Node 181 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator <= 0.252513856822223
## 9: RMD_R10_Denominator > 0.156944484759585
## -----------------------------------------------------------------
## Tree 1 Rule 117 Node 137 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > 0.252513856822223
## -----------------------------------------------------------------
## Tree 1 Rule 118 Node 67 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D6 East South Central", "D7 West South Central")
## 5: RMD_Year > 0.421556724672872
## 6: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 119 Node 230 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator <= -0.766085576665803
## -----------------------------------------------------------------
## Tree 1 Rule 120 Node 354 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator > -0.766085576665803
## 11: RMD_R10_Denominator <= -0.255510394742695
## 12: RMD_R10_Denominator <= -0.486847641829088
## 13: RMD_Year <= -0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 121 Node 388 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator > -0.766085576665803
## 11: RMD_R10_Denominator <= -0.255510394742695
## 12: RMD_R10_Denominator <= -0.486847641829088
## 13: RMD_Year > -0.75880210441117
## 14: RMD_R10_Denominator <= -0.639292878004575
## -----------------------------------------------------------------
## Tree 1 Rule 122 Node 389 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator > -0.766085576665803
## 11: RMD_R10_Denominator <= -0.255510394742695
## 12: RMD_R10_Denominator <= -0.486847641829088
## 13: RMD_Year > -0.75880210441117
## 14: RMD_R10_Denominator > -0.639292878004575
## -----------------------------------------------------------------
## Tree 1 Rule 123 Node 323 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator > -0.766085576665803
## 11: RMD_R10_Denominator <= -0.255510394742695
## 12: RMD_R10_Denominator > -0.486847641829088
## -----------------------------------------------------------------
## Tree 1 Rule 124 Node 279 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D4 West North Central")
## 10: RMD_R10_Denominator > -0.766085576665803
## 11: RMD_R10_Denominator > -0.255510394742695
## -----------------------------------------------------------------
## Tree 1 Rule 125 Node 324 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.790572598764216
## 11: RMD_R10_Denominator <= -0.909215426442246
## 12: RMD_R10_Denominator <= -1.723463691276
## -----------------------------------------------------------------
## Tree 1 Rule 126 Node 325 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.790572598764216
## 11: RMD_R10_Denominator <= -0.909215426442246
## 12: RMD_R10_Denominator > -1.723463691276
## -----------------------------------------------------------------
## Tree 1 Rule 127 Node 356 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.790572598764216
## 11: RMD_R10_Denominator > -0.909215426442246
## 12: RMD_Year <= 0.0843113449345744
## 13: RMD_R10_Denominator <= -0.891528632461194
## -----------------------------------------------------------------
## Tree 1 Rule 128 Node 357 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.790572598764216
## 11: RMD_R10_Denominator > -0.909215426442246
## 12: RMD_Year <= 0.0843113449345744
## 13: RMD_R10_Denominator > -0.891528632461194
## -----------------------------------------------------------------
## Tree 1 Rule 129 Node 327 Decision Very High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.790572598764216
## 11: RMD_R10_Denominator > -0.909215426442246
## 12: RMD_Year > 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 130 Node 358 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.790572598764216
## 11: State_Region IN ("D2 Middle Atlantic")
## 12: RMD_Year <= -0.337245379738298
## 13: RMD_R10_Denominator <= 0.165844816496007
## -----------------------------------------------------------------
## Tree 1 Rule 131 Node 359 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.790572598764216
## 11: State_Region IN ("D2 Middle Atlantic")
## 12: RMD_Year <= -0.337245379738298
## 13: RMD_R10_Denominator > 0.165844816496007
## -----------------------------------------------------------------
## Tree 1 Rule 132 Node 329 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.790572598764216
## 11: State_Region IN ("D2 Middle Atlantic")
## 12: RMD_Year > -0.337245379738298
## -----------------------------------------------------------------
## Tree 1 Rule 133 Node 330 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.790572598764216
## 11: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 134 Node 331 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.790572598764216
## 11: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 135 Node 234 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator <= -0.147272210165247
## 10: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 136 Node 284 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator <= -0.147272210165247
## 10: RMD_Year > -0.421556724672872
## 11: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 137 Node 285 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator <= -0.147272210165247
## 10: RMD_Year > -0.421556724672872
## 11: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 138 Node 185 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.496461587694552
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator > -0.147272210165247
## -----------------------------------------------------------------
## Tree 1 Rule 139 Node 99 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > 0.496461587694552
## -----------------------------------------------------------------
## Tree 1 Rule 140 Node 140 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= -0.252934034803723
## 8: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 141 Node 236 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= -0.252934034803723
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator <= 0.486141851515072
## 10: RMD_R10_Denominator <= 0.263075473560747
## -----------------------------------------------------------------
## Tree 1 Rule 142 Node 237 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= -0.252934034803723
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator <= 0.486141851515072
## 10: RMD_R10_Denominator > 0.263075473560747
## -----------------------------------------------------------------
## Tree 1 Rule 143 Node 187 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= -0.252934034803723
## 8: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.486141851515072
## -----------------------------------------------------------------
## Tree 1 Rule 144 Node 286 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator <= 0.236568223289597
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_Year <= 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 145 Node 287 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator <= 0.236568223289597
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_Year > 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 146 Node 239 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator <= 0.236568223289597
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 147 Node 288 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator > 0.236568223289597
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_R10_Denominator <= 0.586955993806266
## -----------------------------------------------------------------
## Tree 1 Rule 148 Node 289 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator > 0.236568223289597
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_R10_Denominator > 0.586955993806266
## -----------------------------------------------------------------
## Tree 1 Rule 149 Node 290 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator > 0.236568223289597
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 150 Node 291 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D4 West North Central", "D8 Mountain")
## 9: RMD_R10_Denominator > 0.236568223289597
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 151 Node 190 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 1 Rule 152 Node 242 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.283145730226754
## -----------------------------------------------------------------
## Tree 1 Rule 153 Node 292 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.283145730226754
## 11: RMD_R10_Denominator <= 0.502531337813605
## -----------------------------------------------------------------
## Tree 1 Rule 154 Node 293 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year <= 0.252934034803723
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > -0.252934034803723
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.283145730226754
## 11: RMD_R10_Denominator > 0.502531337813605
## -----------------------------------------------------------------
## Tree 1 Rule 155 Node 192 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator <= -1.26406193095431
## 8: RMD_Year <= 0.421556724672872
## 9: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 156 Node 193 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator <= -1.26406193095431
## 8: RMD_Year <= 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 157 Node 194 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator <= -1.26406193095431
## 8: RMD_Year > 0.421556724672872
## 9: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 158 Node 244 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator <= -1.26406193095431
## 8: RMD_Year > 0.421556724672872
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator <= -1.42227669777106
## -----------------------------------------------------------------
## Tree 1 Rule 159 Node 245 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator <= -1.26406193095431
## 8: RMD_Year > 0.421556724672872
## 9: RMD_Year > 0.75880210441117
## 10: RMD_R10_Denominator > -1.42227669777106
## -----------------------------------------------------------------
## Tree 1 Rule 160 Node 294 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator <= -0.546812072307521
## 11: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 161 Node 332 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator <= -0.546812072307521
## 11: RMD_Year > 0.421556724672872
## 12: RMD_R10_Denominator <= -1.24495343406708
## -----------------------------------------------------------------
## Tree 1 Rule 162 Node 333 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator <= -0.546812072307521
## 11: RMD_Year > 0.421556724672872
## 12: RMD_R10_Denominator > -1.24495343406708
## -----------------------------------------------------------------
## Tree 1 Rule 163 Node 334 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator > -0.546812072307521
## 11: RMD_Year <= 0.421556724672872
## 12: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 164 Node 360 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator > -0.546812072307521
## 11: RMD_Year <= 0.421556724672872
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator <= -0.241412193412383
## -----------------------------------------------------------------
## Tree 1 Rule 165 Node 361 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator > -0.546812072307521
## 11: RMD_Year <= 0.421556724672872
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator > -0.241412193412383
## -----------------------------------------------------------------
## Tree 1 Rule 166 Node 297 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.590179414542021
## 10: RMD_R10_Denominator > -0.546812072307521
## 11: RMD_Year > 0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 167 Node 362 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator <= -0.441771297137185
## 11: State_Region IN ("D4 West North Central", "D8 Mountain")
## 12: State_Region IN ("D4 West North Central")
## 13: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 168 Node 363 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator <= -0.441771297137185
## 11: State_Region IN ("D4 West North Central", "D8 Mountain")
## 12: State_Region IN ("D4 West North Central")
## 13: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 169 Node 364 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator <= -0.441771297137185
## 11: State_Region IN ("D4 West North Central", "D8 Mountain")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator <= -0.56973509497047
## -----------------------------------------------------------------
## Tree 1 Rule 170 Node 365 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator <= -0.441771297137185
## 11: State_Region IN ("D4 West North Central", "D8 Mountain")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator > -0.56973509497047
## -----------------------------------------------------------------
## Tree 1 Rule 171 Node 299 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator <= -0.441771297137185
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 172 Node 249 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("medi")
## 9: RMD_Year > 0.590179414542021
## 10: RMD_R10_Denominator > -0.441771297137185
## -----------------------------------------------------------------
## Tree 1 Rule 173 Node 250 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D8 Mountain")
## 10: RMD_R10_Denominator <= -0.884949498593253
## -----------------------------------------------------------------
## Tree 1 Rule 174 Node 366 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D8 Mountain")
## 10: RMD_R10_Denominator > -0.884949498593253
## 11: RMD_R10_Denominator <= -0.708417781304018
## 12: RMD_R10_Denominator <= -0.757612493806227
## 13: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 175 Node 367 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D8 Mountain")
## 10: RMD_R10_Denominator > -0.884949498593253
## 11: RMD_R10_Denominator <= -0.708417781304018
## 12: RMD_R10_Denominator <= -0.757612493806227
## 13: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 176 Node 339 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D8 Mountain")
## 10: RMD_R10_Denominator > -0.884949498593253
## 11: RMD_R10_Denominator <= -0.708417781304018
## 12: RMD_R10_Denominator > -0.757612493806227
## -----------------------------------------------------------------
## Tree 1 Rule 177 Node 301 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D8 Mountain")
## 10: RMD_R10_Denominator > -0.884949498593253
## 11: RMD_R10_Denominator > -0.708417781304018
## -----------------------------------------------------------------
## Tree 1 Rule 178 Node 199 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator <= -0.177550392083333
## 7: RMD_R10_Denominator > -1.26406193095431
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 179 Node 200 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("medi")
## 9: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 1 Rule 180 Node 252 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("medi")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator <= 0.127996752686139
## -----------------------------------------------------------------
## Tree 1 Rule 181 Node 253 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("medi")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator > 0.127996752686139
## -----------------------------------------------------------------
## Tree 1 Rule 182 Node 254 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator <= 0.459904750603279
## -----------------------------------------------------------------
## Tree 1 Rule 183 Node 302 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator > 0.459904750603279
## 11: RMD_R10_Denominator <= 0.569064137361579
## -----------------------------------------------------------------
## Tree 1 Rule 184 Node 303 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator > 0.459904750603279
## 11: RMD_R10_Denominator > 0.569064137361579
## -----------------------------------------------------------------
## Tree 1 Rule 185 Node 256 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > 1.43329286388776
## 10: RMD_R10_Denominator <= 0.37407917117993
## -----------------------------------------------------------------
## Tree 1 Rule 186 Node 257 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D8 Mountain")
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > 1.43329286388776
## 10: RMD_R10_Denominator > 0.37407917117993
## -----------------------------------------------------------------
## Tree 1 Rule 187 Node 204 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator <= 0.0395957752274338
## -----------------------------------------------------------------
## Tree 1 Rule 188 Node 368 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("medi")
## 11: State_Region IN ("D2 Middle Atlantic", "D4 West North Central")
## 12: RMD_Year <= 0.75880210441117
## 13: RMD_R10_Denominator <= 0.444272042570772
## -----------------------------------------------------------------
## Tree 1 Rule 189 Node 369 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("medi")
## 11: State_Region IN ("D2 Middle Atlantic", "D4 West North Central")
## 12: RMD_Year <= 0.75880210441117
## 13: RMD_R10_Denominator > 0.444272042570772
## -----------------------------------------------------------------
## Tree 1 Rule 190 Node 341 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("medi")
## 11: State_Region IN ("D2 Middle Atlantic", "D4 West North Central")
## 12: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 191 Node 305 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("medi")
## 11: State_Region IN ("D1 New England", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 192 Node 390 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 0.582271271465595
## 12: State_Region IN ("D4 West North Central")
## 13: RMD_R10_Denominator <= 0.352322847346197
## 14: RMD_R10_Denominator <= 0.137516148681095
## -----------------------------------------------------------------
## Tree 1 Rule 193 Node 391 Decision Low
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 0.582271271465595
## 12: State_Region IN ("D4 West North Central")
## 13: RMD_R10_Denominator <= 0.352322847346197
## 14: RMD_R10_Denominator > 0.137516148681095
## -----------------------------------------------------------------
## Tree 1 Rule 194 Node 371 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 0.582271271465595
## 12: State_Region IN ("D4 West North Central")
## 13: RMD_R10_Denominator > 0.352322847346197
## -----------------------------------------------------------------
## Tree 1 Rule 195 Node 343 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 0.582271271465595
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 196 Node 392 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 0.582271271465595
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator <= 1.25804514163807
## 14: RMD_R10_Denominator <= 0.889573482965707
## -----------------------------------------------------------------
## Tree 1 Rule 197 Node 393 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 0.582271271465595
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator <= 1.25804514163807
## 14: RMD_R10_Denominator > 0.889573482965707
## -----------------------------------------------------------------
## Tree 1 Rule 198 Node 373 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 0.582271271465595
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator > 1.25804514163807
## -----------------------------------------------------------------
## Tree 1 Rule 199 Node 374 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 0.582271271465595
## 12: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator <= 2.02123980939573
## -----------------------------------------------------------------
## Tree 1 Rule 200 Node 375 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_R10_Denominator > 0.0395957752274338
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 0.582271271465595
## 12: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator > 2.02123980939573
## -----------------------------------------------------------------
## Tree 1 Rule 201 Node 260 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > 1.09604748414947
## 9: RMD_R10_Denominator <= 0.226365412067899
## 10: RMD_R10_Denominator <= -0.00874739992683114
## -----------------------------------------------------------------
## Tree 1 Rule 202 Node 261 Decision Medium
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > 1.09604748414947
## 9: RMD_R10_Denominator <= 0.226365412067899
## 10: RMD_R10_Denominator > -0.00874739992683114
## -----------------------------------------------------------------
## Tree 1 Rule 203 Node 207 Decision High
##  
## 1: RMD_R10_Denominator > -3.86457272986912
## 2: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 3: Source IN ("medi", "sped")
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 5: RMD_Year > 0.252934034803723
## 6: RMD_R10_Denominator > -0.177550392083333
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > 1.09604748414947
## 9: RMD_R10_Denominator > 0.226365412067899
## -----------------------------------------------------------------
## Number of rules in Tree 1: 203
## 
## Random Forest Model 2 
## 
## -------------------------------------------------------------
## Tree 2 Rule 1 Node 32 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D1 New England", "D7 West South Central")
## 4: State_Region IN ("D1 New England")
## 5: RMD_R10_Denominator <= -3.94541050477274
## -----------------------------------------------------------------
## Tree 2 Rule 2 Node 33 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D1 New England", "D7 West South Central")
## 4: State_Region IN ("D1 New England")
## 5: RMD_R10_Denominator > -3.94541050477274
## -----------------------------------------------------------------
## Tree 2 Rule 3 Node 17 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D1 New England", "D7 West South Central")
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 4 Node 34 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year <= -0.168622689869149
## -----------------------------------------------------------------
## Tree 2 Rule 5 Node 94 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year <= 0.505868069607446
## -----------------------------------------------------------------
## Tree 2 Rule 6 Node 258 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year > 0.505868069607446
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator <= -3.93429345225739
## 10: RMD_R10_Denominator <= -3.95099109152159
## -----------------------------------------------------------------
## Tree 2 Rule 7 Node 259 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year > 0.505868069607446
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator <= -3.93429345225739
## 10: RMD_R10_Denominator > -3.95099109152159
## -----------------------------------------------------------------
## Tree 2 Rule 8 Node 195 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year > 0.505868069607446
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator > -3.93429345225739
## -----------------------------------------------------------------
## Tree 2 Rule 9 Node 196 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year > 0.505868069607446
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator <= -3.93220561608781
## -----------------------------------------------------------------
## Tree 2 Rule 10 Node 197 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 7: RMD_Year > 0.505868069607446
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > -3.93220561608781
## -----------------------------------------------------------------
## Tree 2 Rule 11 Node 198 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 7: RMD_R10_Denominator <= -3.87010221155632
## 8: RMD_Year <= 0.505868069607446
## 9: RMD_R10_Denominator <= -3.9523829840435
## -----------------------------------------------------------------
## Tree 2 Rule 12 Node 199 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 7: RMD_R10_Denominator <= -3.87010221155632
## 8: RMD_Year <= 0.505868069607446
## 9: RMD_R10_Denominator > -3.9523829840435
## -----------------------------------------------------------------
## Tree 2 Rule 13 Node 200 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 7: RMD_R10_Denominator <= -3.87010221155632
## 8: RMD_Year > 0.505868069607446
## 9: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 14 Node 201 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 7: RMD_R10_Denominator <= -3.87010221155632
## 8: RMD_Year > 0.505868069607446
## 9: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 15 Node 97 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.18035882908404
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 7: RMD_R10_Denominator > -3.87010221155632
## -----------------------------------------------------------------
## Tree 2 Rule 16 Node 19 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator <= -2.83282007541192
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.18035882908404
## -----------------------------------------------------------------
## Tree 2 Rule 17 Node 36 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year <= -0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 18 Node 98 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year > -0.337245379738298
## 6: RMD_R10_Denominator <= -1.62500066690616
## 7: RMD_R10_Denominator <= -2.08718711410522
## -----------------------------------------------------------------
## Tree 2 Rule 19 Node 142 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year > -0.337245379738298
## 6: RMD_R10_Denominator <= -1.62500066690616
## 7: RMD_R10_Denominator > -2.08718711410522
## 8: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 20 Node 202 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year > -0.337245379738298
## 6: RMD_R10_Denominator <= -1.62500066690616
## 7: RMD_R10_Denominator > -2.08718711410522
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator <= -2.00098749831043
## -----------------------------------------------------------------
## Tree 2 Rule 21 Node 203 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year > -0.337245379738298
## 6: RMD_R10_Denominator <= -1.62500066690616
## 7: RMD_R10_Denominator > -2.08718711410522
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > -2.00098749831043
## -----------------------------------------------------------------
## Tree 2 Rule 22 Node 63 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain")
## 5: RMD_Year > -0.337245379738298
## 6: RMD_R10_Denominator > -1.62500066690616
## -----------------------------------------------------------------
## Tree 2 Rule 23 Node 38 Decision Low
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D1 New England", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 5: RMD_Year <= -0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 24 Node 39 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year <= 0
## 4: State_Region IN ("D1 New England", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 5: RMD_Year > -0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 25 Node 40 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator <= -1.98995068078469
## 5: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 2 Rule 26 Node 41 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator <= -1.98995068078469
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 27 Node 42 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 28 Node 144 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 8: RMD_R10_Denominator <= -1.82807243969889
## -----------------------------------------------------------------
## Tree 2 Rule 29 Node 260 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 8: RMD_R10_Denominator > -1.82807243969889
## 9: RMD_Year <= 0.337245379738298
## 10: RMD_R10_Denominator <= -1.72261654953943
## -----------------------------------------------------------------
## Tree 2 Rule 30 Node 261 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 8: RMD_R10_Denominator > -1.82807243969889
## 9: RMD_Year <= 0.337245379738298
## 10: RMD_R10_Denominator > -1.72261654953943
## -----------------------------------------------------------------
## Tree 2 Rule 31 Node 205 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 8: RMD_R10_Denominator > -1.82807243969889
## 9: RMD_Year > 0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 32 Node 146 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 33 Node 206 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.337245379738298
## 9: RMD_R10_Denominator <= -1.65377309708709
## -----------------------------------------------------------------
## Tree 2 Rule 34 Node 207 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.337245379738298
## 9: RMD_R10_Denominator > -1.65377309708709
## -----------------------------------------------------------------
## Tree 2 Rule 35 Node 65 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_R10_Denominator > -2.83282007541192
## 3: RMD_Year > 0
## 4: RMD_R10_Denominator > -1.98995068078469
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.674490759476595
## -----------------------------------------------------------------
## Tree 2 Rule 36 Node 102 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator <= -1.17993496957465
## 7: RMD_R10_Denominator <= -1.66668083958478
## -----------------------------------------------------------------
## Tree 2 Rule 37 Node 103 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator <= -1.17993496957465
## 7: RMD_R10_Denominator > -1.66668083958478
## -----------------------------------------------------------------
## Tree 2 Rule 38 Node 148 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator > -1.17993496957465
## 7: Source IN ("medi")
## 8: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 2 Rule 39 Node 208 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator > -1.17993496957465
## 7: Source IN ("medi")
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator <= -1.07559181974014
## -----------------------------------------------------------------
## Tree 2 Rule 40 Node 262 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator > -1.17993496957465
## 7: Source IN ("medi")
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > -1.07559181974014
## 10: RMD_R10_Denominator <= -0.806360838564277
## -----------------------------------------------------------------
## Tree 2 Rule 41 Node 263 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator > -1.17993496957465
## 7: Source IN ("medi")
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > -1.07559181974014
## 10: RMD_R10_Denominator > -0.806360838564277
## -----------------------------------------------------------------
## Tree 2 Rule 42 Node 105 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D1 New England", "D8 Mountain")
## 6: RMD_R10_Denominator > -1.17993496957465
## 7: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 2 Rule 43 Node 150 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= -0.768111307217666
## 8: RMD_R10_Denominator <= -1.7325271101552
## -----------------------------------------------------------------
## Tree 2 Rule 44 Node 210 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= -0.768111307217666
## 8: RMD_R10_Denominator > -1.7325271101552
## 9: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 45 Node 314 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= -0.768111307217666
## 8: RMD_R10_Denominator > -1.7325271101552
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= -1.26971606689474
## 11: RMD_R10_Denominator <= -1.30558717479423
## -----------------------------------------------------------------
## Tree 2 Rule 46 Node 315 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= -0.768111307217666
## 8: RMD_R10_Denominator > -1.7325271101552
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= -1.26971606689474
## 11: RMD_R10_Denominator > -1.30558717479423
## -----------------------------------------------------------------
## Tree 2 Rule 47 Node 265 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= -0.768111307217666
## 8: RMD_R10_Denominator > -1.7325271101552
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator > -1.26971606689474
## -----------------------------------------------------------------
## Tree 2 Rule 48 Node 152 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > -0.768111307217666
## 8: RMD_R10_Denominator <= -0.731761097408073
## -----------------------------------------------------------------
## Tree 2 Rule 49 Node 153 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > -0.768111307217666
## 8: RMD_R10_Denominator > -0.731761097408073
## -----------------------------------------------------------------
## Tree 2 Rule 50 Node 69 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year <= -0.0843113449345744
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 2 Rule 51 Node 212 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 52 Node 266 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator <= -1.48061531018735
## -----------------------------------------------------------------
## Tree 2 Rule 53 Node 316 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator > -1.48061531018735
## 11: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 2 Rule 54 Node 317 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator > -1.48061531018735
## 11: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 55 Node 318 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year <= 0.421556724672872
## 10: RMD_R10_Denominator <= -1.31581623092771
## 11: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 56 Node 319 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year <= 0.421556724672872
## 10: RMD_R10_Denominator <= -1.31581623092771
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 57 Node 269 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year <= 0.421556724672872
## 10: RMD_R10_Denominator > -1.31581623092771
## -----------------------------------------------------------------
## Tree 2 Rule 58 Node 320 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator <= -1.24263022847202
## 11: RMD_Year <= 1.09604748414947
## -----------------------------------------------------------------
## Tree 2 Rule 59 Node 321 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator <= -1.24263022847202
## 11: RMD_Year > 1.09604748414947
## -----------------------------------------------------------------
## Tree 2 Rule 60 Node 322 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator > -1.24263022847202
## 11: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 61 Node 323 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator <= -1.22190757192299
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.421556724672872
## 10: RMD_R10_Denominator > -1.24263022847202
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 62 Node 109 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator <= -1.09928685570431
## 7: RMD_R10_Denominator > -1.22190757192299
## -----------------------------------------------------------------
## Tree 2 Rule 63 Node 272 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator <= -0.956732745363231
## 10: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 2 Rule 64 Node 324 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator <= -0.956732745363231
## 10: Source IN ("addm", "nsch", "sped")
## 11: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 2 Rule 65 Node 354 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator <= -0.956732745363231
## 10: Source IN ("addm", "nsch", "sped")
## 11: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_R10_Denominator <= -1.07950518357392
## -----------------------------------------------------------------
## Tree 2 Rule 66 Node 355 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator <= -0.956732745363231
## 10: Source IN ("addm", "nsch", "sped")
## 11: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_R10_Denominator > -1.07950518357392
## -----------------------------------------------------------------
## Tree 2 Rule 67 Node 274 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator > -0.956732745363231
## 10: RMD_R10_Denominator <= -0.893420170624845
## -----------------------------------------------------------------
## Tree 2 Rule 68 Node 275 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D1 New England", "D8 Mountain")
## 9: RMD_R10_Denominator > -0.956732745363231
## 10: RMD_R10_Denominator > -0.893420170624845
## -----------------------------------------------------------------
## Tree 2 Rule 69 Node 218 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 2 Rule 70 Node 276 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.252934034803723
## 10: RMD_R10_Denominator <= -0.966281303924519
## -----------------------------------------------------------------
## Tree 2 Rule 71 Node 277 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator <= -0.82659597279537
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 9: RMD_Year > 0.252934034803723
## 10: RMD_R10_Denominator > -0.966281303924519
## -----------------------------------------------------------------
## Tree 2 Rule 72 Node 158 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator > -0.82659597279537
## 8: RMD_R10_Denominator <= -0.789295541755423
## -----------------------------------------------------------------
## Tree 2 Rule 73 Node 220 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator > -0.82659597279537
## 8: RMD_R10_Denominator > -0.789295541755423
## 9: RMD_Year <= 0.927424794280318
## -----------------------------------------------------------------
## Tree 2 Rule 74 Node 278 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator > -0.82659597279537
## 8: RMD_R10_Denominator > -0.789295541755423
## 9: RMD_Year > 0.927424794280318
## 10: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 75 Node 279 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator <= -0.770036823455363
## 6: RMD_R10_Denominator > -1.09928685570431
## 7: RMD_R10_Denominator > -0.82659597279537
## 8: RMD_R10_Denominator > -0.789295541755423
## 9: RMD_Year > 0.927424794280318
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 76 Node 112 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator > -0.770036823455363
## 6: RMD_R10_Denominator <= -0.721971740213964
## 7: State_Region IN ("D1 New England", "D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 77 Node 113 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator > -0.770036823455363
## 6: RMD_R10_Denominator <= -0.721971740213964
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 78 Node 73 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator <= -0.711587047894901
## 4: RMD_Year > -0.0843113449345744
## 5: RMD_R10_Denominator > -0.770036823455363
## 6: RMD_R10_Denominator > -0.721971740213964
## -----------------------------------------------------------------
## Tree 2 Rule 79 Node 74 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= -0.66046296250219
## -----------------------------------------------------------------
## Tree 2 Rule 80 Node 75 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > -0.66046296250219
## -----------------------------------------------------------------
## Tree 2 Rule 81 Node 160 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D5 South Atlantic")
## 8: RMD_Year <= -0.843113449345744
## -----------------------------------------------------------------
## Tree 2 Rule 82 Node 161 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D5 South Atlantic")
## 8: RMD_Year > -0.843113449345744
## -----------------------------------------------------------------
## Tree 2 Rule 83 Node 162 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 84 Node 222 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator <= -0.639292878004575
## -----------------------------------------------------------------
## Tree 2 Rule 85 Node 326 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator > -0.639292878004575
## 10: State_Region IN ("D4 West North Central", "D7 West South Central")
## 11: RMD_R10_Denominator <= -0.20375858826309
## -----------------------------------------------------------------
## Tree 2 Rule 86 Node 327 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator > -0.639292878004575
## 10: State_Region IN ("D4 West North Central", "D7 West South Central")
## 11: RMD_R10_Denominator > -0.20375858826309
## -----------------------------------------------------------------
## Tree 2 Rule 87 Node 281 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.75880210441117
## 9: RMD_R10_Denominator > -0.639292878004575
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 88 Node 77 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D9 Pacific")
## 6: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 2 Rule 89 Node 224 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year <= 0.421556724672872
## 8: RMD_R10_Denominator <= -0.663833511295947
## 9: RMD_R10_Denominator <= -0.670552964966762
## -----------------------------------------------------------------
## Tree 2 Rule 90 Node 225 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year <= 0.421556724672872
## 8: RMD_R10_Denominator <= -0.663833511295947
## 9: RMD_R10_Denominator > -0.670552964966762
## -----------------------------------------------------------------
## Tree 2 Rule 91 Node 165 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year <= 0.421556724672872
## 8: RMD_R10_Denominator > -0.663833511295947
## -----------------------------------------------------------------
## Tree 2 Rule 92 Node 226 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year > 0.421556724672872
## 8: RMD_R10_Denominator <= -0.615343083785191
## 9: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 93 Node 282 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year > 0.421556724672872
## 8: RMD_R10_Denominator <= -0.615343083785191
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 94 Node 283 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year > 0.421556724672872
## 8: RMD_R10_Denominator <= -0.615343083785191
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 95 Node 228 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year > 0.421556724672872
## 8: RMD_R10_Denominator > -0.615343083785191
## 9: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 96 Node 229 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator <= -0.518728781924273
## 7: RMD_Year > 0.421556724672872
## 8: RMD_R10_Denominator > -0.615343083785191
## 9: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 97 Node 118 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator <= -0.508242054967308
## -----------------------------------------------------------------
## Tree 2 Rule 98 Node 230 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year <= 0.252934034803723
## 9: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 2 Rule 99 Node 284 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year <= 0.252934034803723
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator <= -0.450759690109325
## -----------------------------------------------------------------
## Tree 2 Rule 100 Node 328 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year <= 0.252934034803723
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.450759690109325
## 11: RMD_R10_Denominator <= -0.226383530602004
## -----------------------------------------------------------------
## Tree 2 Rule 101 Node 356 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year <= 0.252934034803723
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.450759690109325
## 11: RMD_R10_Denominator > -0.226383530602004
## 12: RMD_R10_Denominator <= -0.225154632825403
## -----------------------------------------------------------------
## Tree 2 Rule 102 Node 357 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year <= 0.252934034803723
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator > -0.450759690109325
## 11: RMD_R10_Denominator > -0.226383530602004
## 12: RMD_R10_Denominator > -0.225154632825403
## -----------------------------------------------------------------
## Tree 2 Rule 103 Node 358 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D5 South Atlantic", "D8 Mountain")
## 11: Source IN ("medi")
## 12: RMD_R10_Denominator <= -0.22218425217939
## -----------------------------------------------------------------
## Tree 2 Rule 104 Node 359 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D5 South Atlantic", "D8 Mountain")
## 11: Source IN ("medi")
## 12: RMD_R10_Denominator > -0.22218425217939
## -----------------------------------------------------------------
## Tree 2 Rule 105 Node 360 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D5 South Atlantic", "D8 Mountain")
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 2 Rule 106 Node 380 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D5 South Atlantic", "D8 Mountain")
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_R10_Denominator <= -0.259459421524286
## -----------------------------------------------------------------
## Tree 2 Rule 107 Node 381 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D5 South Atlantic", "D8 Mountain")
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_R10_Denominator > -0.259459421524286
## -----------------------------------------------------------------
## Tree 2 Rule 108 Node 287 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year <= 0.590179414542021
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 109 Node 233 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator <= -0.170856853660262
## 6: RMD_R10_Denominator > -0.518728781924273
## 7: RMD_R10_Denominator > -0.508242054967308
## 8: RMD_Year > 0.252934034803723
## 9: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 110 Node 51 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator <= -0.13846253975302
## 3: RMD_R10_Denominator > -0.711587047894901
## 4: RMD_Year > -0.252934034803723
## 5: RMD_R10_Denominator > -0.170856853660262
## -----------------------------------------------------------------
## Tree 2 Rule 111 Node 80 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator <= -0.0708784245519317
## -----------------------------------------------------------------
## Tree 2 Rule 112 Node 288 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator <= -0.0546678681224847
## 8: RMD_Year <= -0.0843113449345744
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator <= -0.0598664467463477
## -----------------------------------------------------------------
## Tree 2 Rule 113 Node 289 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator <= -0.0546678681224847
## 8: RMD_Year <= -0.0843113449345744
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator > -0.0598664467463477
## -----------------------------------------------------------------
## Tree 2 Rule 114 Node 235 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator <= -0.0546678681224847
## 8: RMD_Year <= -0.0843113449345744
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 115 Node 171 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator <= -0.0546678681224847
## 8: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 2 Rule 116 Node 290 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year <= 0
## 9: RMD_R10_Denominator <= 0.00877416613285446
## 10: RMD_Year <= -0.505868069607446
## -----------------------------------------------------------------
## Tree 2 Rule 117 Node 332 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year <= 0
## 9: RMD_R10_Denominator <= 0.00877416613285446
## 10: RMD_Year > -0.505868069607446
## 11: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 118 Node 333 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year <= 0
## 9: RMD_R10_Denominator <= 0.00877416613285446
## 10: RMD_Year > -0.505868069607446
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 119 Node 237 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year <= 0
## 9: RMD_R10_Denominator > 0.00877416613285446
## -----------------------------------------------------------------
## Tree 2 Rule 120 Node 238 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year > 0
## 9: RMD_R10_Denominator <= -0.0303145421316482
## -----------------------------------------------------------------
## Tree 2 Rule 121 Node 239 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator <= 0.0138489521079779
## 6: RMD_R10_Denominator > -0.0708784245519317
## 7: RMD_R10_Denominator > -0.0546678681224847
## 8: RMD_Year > 0
## 9: RMD_R10_Denominator > -0.0303145421316482
## -----------------------------------------------------------------
## Tree 2 Rule 122 Node 82 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 123 Node 122 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D6 East South Central", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 2 Rule 124 Node 292 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## 9: Source IN ("medi")
## 10: RMD_R10_Denominator <= 0.357413433046109
## -----------------------------------------------------------------
## Tree 2 Rule 125 Node 293 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## 9: Source IN ("medi")
## 10: RMD_R10_Denominator > 0.357413433046109
## -----------------------------------------------------------------
## Tree 2 Rule 126 Node 294 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.49514874700187
## -----------------------------------------------------------------
## Tree 2 Rule 127 Node 334 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.49514874700187
## 11: RMD_R10_Denominator <= 0.652590173981348
## -----------------------------------------------------------------
## Tree 2 Rule 128 Node 335 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.49514874700187
## 11: RMD_R10_Denominator > 0.652590173981348
## -----------------------------------------------------------------
## Tree 2 Rule 129 Node 336 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## 9: RMD_R10_Denominator <= 0.81413547554832
## 10: RMD_R10_Denominator <= 0.469860110871562
## 11: RMD_R10_Denominator <= 0.135462604517625
## -----------------------------------------------------------------
## Tree 2 Rule 130 Node 337 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## 9: RMD_R10_Denominator <= 0.81413547554832
## 10: RMD_R10_Denominator <= 0.469860110871562
## 11: RMD_R10_Denominator > 0.135462604517625
## -----------------------------------------------------------------
## Tree 2 Rule 131 Node 297 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## 9: RMD_R10_Denominator <= 0.81413547554832
## 10: RMD_R10_Denominator > 0.469860110871562
## -----------------------------------------------------------------
## Tree 2 Rule 132 Node 298 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## 9: RMD_R10_Denominator > 0.81413547554832
## 10: RMD_R10_Denominator <= 1.18429292309359
## -----------------------------------------------------------------
## Tree 2 Rule 133 Node 299 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= 0.252934034803723
## 5: RMD_R10_Denominator > 0.0138489521079779
## 6: RMD_Year > -0.421556724672872
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## 9: RMD_R10_Denominator > 0.81413547554832
## 10: RMD_R10_Denominator > 1.18429292309359
## -----------------------------------------------------------------
## Tree 2 Rule 134 Node 176 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.379599314986533
## 8: RMD_R10_Denominator <= 0.174535140506537
## -----------------------------------------------------------------
## Tree 2 Rule 135 Node 177 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.379599314986533
## 8: RMD_R10_Denominator > 0.174535140506537
## -----------------------------------------------------------------
## Tree 2 Rule 136 Node 125 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > 0.379599314986533
## -----------------------------------------------------------------
## Tree 2 Rule 137 Node 178 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator <= 0.522459936864327
## 8: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 138 Node 179 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator <= 0.522459936864327
## 8: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 139 Node 244 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.522459936864327
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 140 Node 245 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.522459936864327
## 8: RMD_Year <= 1.09604748414947
## 9: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 141 Node 181 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D5 South Atlantic")
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_R10_Denominator > 0.522459936864327
## 8: RMD_Year > 1.09604748414947
## -----------------------------------------------------------------
## Tree 2 Rule 142 Node 246 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator <= 0.0465488278601548
## 9: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 143 Node 300 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator <= 0.0465488278601548
## 9: RMD_Year > 0.75880210441117
## 10: State_Region IN ("D7 West South Central")
## -----------------------------------------------------------------
## Tree 2 Rule 144 Node 301 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator <= 0.0465488278601548
## 9: RMD_Year > 0.75880210441117
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 145 Node 248 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator <= 0.300869882656342
## -----------------------------------------------------------------
## Tree 2 Rule 146 Node 338 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator > 0.300869882656342
## 10: State_Region IN ("D6 East South Central", "D7 West South Central")
## 11: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 147 Node 382 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator > 0.300869882656342
## 10: State_Region IN ("D6 East South Central", "D7 West South Central")
## 11: RMD_Year > 0.590179414542021
## 12: RMD_Year <= 0.75880210441117
## 13: RMD_R10_Denominator <= 0.362343928514155
## -----------------------------------------------------------------
## Tree 2 Rule 148 Node 383 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator > 0.300869882656342
## 10: State_Region IN ("D6 East South Central", "D7 West South Central")
## 11: RMD_Year > 0.590179414542021
## 12: RMD_Year <= 0.75880210441117
## 13: RMD_R10_Denominator > 0.362343928514155
## -----------------------------------------------------------------
## Tree 2 Rule 149 Node 363 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator > 0.300869882656342
## 10: State_Region IN ("D6 East South Central", "D7 West South Central")
## 11: RMD_Year > 0.590179414542021
## 12: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 150 Node 303 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("medi")
## 8: RMD_R10_Denominator > 0.0465488278601548
## 9: RMD_R10_Denominator > 0.300869882656342
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 151 Node 184 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator <= -0.0180889701615911
## -----------------------------------------------------------------
## Tree 2 Rule 152 Node 250 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator <= 0.150754457672401
## -----------------------------------------------------------------
## Tree 2 Rule 153 Node 304 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator <= 0.224810333481062
## -----------------------------------------------------------------
## Tree 2 Rule 154 Node 340 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator > 0.224810333481062
## 11: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 155 Node 384 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator > 0.224810333481062
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D8 Mountain")
## 13: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 156 Node 400 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator > 0.224810333481062
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D8 Mountain")
## 13: RMD_Year > 0.590179414542021
## 14: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 157 Node 401 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator > 0.224810333481062
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D8 Mountain")
## 13: RMD_Year > 0.590179414542021
## 14: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 158 Node 365 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.927424794280318
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_R10_Denominator > -0.0180889701615911
## 9: RMD_R10_Denominator > 0.150754457672401
## 10: RMD_R10_Denominator > 0.224810333481062
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 159 Node 87 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > 0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 2 Rule 160 Node 402 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## 11: RMD_R10_Denominator <= 0.554672082243324
## 12: RMD_Year <= -0.75880210441117
## 13: RMD_R10_Denominator <= 0.388046750679523
## 14: RMD_R10_Denominator <= 0.361313015791588
## -----------------------------------------------------------------
## Tree 2 Rule 161 Node 403 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## 11: RMD_R10_Denominator <= 0.554672082243324
## 12: RMD_Year <= -0.75880210441117
## 13: RMD_R10_Denominator <= 0.388046750679523
## 14: RMD_R10_Denominator > 0.361313015791588
## -----------------------------------------------------------------
## Tree 2 Rule 162 Node 387 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## 11: RMD_R10_Denominator <= 0.554672082243324
## 12: RMD_Year <= -0.75880210441117
## 13: RMD_R10_Denominator > 0.388046750679523
## -----------------------------------------------------------------
## Tree 2 Rule 163 Node 367 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## 11: RMD_R10_Denominator <= 0.554672082243324
## 12: RMD_Year > -0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 164 Node 343 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## 11: RMD_R10_Denominator > 0.554672082243324
## -----------------------------------------------------------------
## Tree 2 Rule 165 Node 307 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.0843113449345744
## 10: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 166 Node 388 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D3 East North Central", "D4 West North Central")
## 13: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 167 Node 404 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D3 East North Central", "D4 West North Central")
## 13: RMD_Year > 0.421556724672872
## 14: RMD_R10_Denominator <= 0.0346977248193588
## -----------------------------------------------------------------
## Tree 2 Rule 168 Node 405 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D3 East North Central", "D4 West North Central")
## 13: RMD_Year > 0.421556724672872
## 14: RMD_R10_Denominator > 0.0346977248193588
## -----------------------------------------------------------------
## Tree 2 Rule 169 Node 390 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 2 Rule 170 Node 414 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_Year > 0.252934034803723
## 14: RMD_Year <= 0.505868069607446
## 15: RMD_R10_Denominator <= 0.363288303191411
## -----------------------------------------------------------------
## Tree 2 Rule 171 Node 415 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_Year > 0.252934034803723
## 14: RMD_Year <= 0.505868069607446
## 15: RMD_R10_Denominator > 0.363288303191411
## -----------------------------------------------------------------
## Tree 2 Rule 172 Node 407 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_Year > 0.252934034803723
## 14: RMD_Year > 0.505868069607446
## -----------------------------------------------------------------
## Tree 2 Rule 173 Node 345 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central")
## 11: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 2 Rule 174 Node 346 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D1 New England", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 175 Node 370 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D1 New England", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > 0.421556724672872
## 12: RMD_R10_Denominator <= 0.246710170914432
## -----------------------------------------------------------------
## Tree 2 Rule 176 Node 371 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("medi")
## 9: RMD_Year > -0.0843113449345744
## 10: State_Region IN ("D1 New England", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > 0.421556724672872
## 12: RMD_R10_Denominator > 0.246710170914432
## -----------------------------------------------------------------
## Tree 2 Rule 177 Node 348 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator <= 0.266898067202569
## -----------------------------------------------------------------
## Tree 2 Rule 178 Node 392 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year <= -0.75880210441117
## 13: RMD_R10_Denominator <= 0.273648134902801
## -----------------------------------------------------------------
## Tree 2 Rule 179 Node 393 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year <= -0.75880210441117
## 13: RMD_R10_Denominator > 0.273648134902801
## -----------------------------------------------------------------
## Tree 2 Rule 180 Node 394 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year > -0.75880210441117
## 13: RMD_Year <= -0.590179414542021
## -----------------------------------------------------------------
## Tree 2 Rule 181 Node 408 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year > -0.75880210441117
## 13: RMD_Year > -0.590179414542021
## 14: RMD_R10_Denominator <= 0.27663306609095
## -----------------------------------------------------------------
## Tree 2 Rule 182 Node 416 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year > -0.75880210441117
## 13: RMD_Year > -0.590179414542021
## 14: RMD_R10_Denominator > 0.27663306609095
## 15: RMD_R10_Denominator <= 0.424469452699812
## -----------------------------------------------------------------
## Tree 2 Rule 183 Node 417 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator <= 0.570713704720424
## 11: RMD_R10_Denominator > 0.266898067202569
## 12: RMD_Year > -0.75880210441117
## 13: RMD_Year > -0.590179414542021
## 14: RMD_R10_Denominator > 0.27663306609095
## 15: RMD_R10_Denominator > 0.424469452699812
## -----------------------------------------------------------------
## Tree 2 Rule 184 Node 311 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year <= -0.421556724672872
## 10: RMD_R10_Denominator > 0.570713704720424
## -----------------------------------------------------------------
## Tree 2 Rule 185 Node 396 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator <= 0.274186685412876
## 13: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 2 Rule 186 Node 418 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator <= 0.274186685412876
## 13: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.138659216618865
## 15: RMD_Year <= 0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 187 Node 419 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator <= 0.274186685412876
## 13: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.138659216618865
## 15: RMD_Year > 0.337245379738298
## -----------------------------------------------------------------
## Tree 2 Rule 188 Node 411 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator <= 0.274186685412876
## 13: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.138659216618865
## -----------------------------------------------------------------
## Tree 2 Rule 189 Node 412 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator > 0.274186685412876
## 13: RMD_R10_Denominator <= 0.560798452640123
## 14: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 2 Rule 190 Node 413 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator > 0.274186685412876
## 13: RMD_R10_Denominator <= 0.560798452640123
## 14: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 2 Rule 191 Node 399 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year <= 0.927424794280318
## 12: RMD_R10_Denominator > 0.274186685412876
## 13: RMD_R10_Denominator > 0.560798452640123
## -----------------------------------------------------------------
## Tree 2 Rule 192 Node 376 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year > 0.927424794280318
## 12: RMD_R10_Denominator <= 0.188487766678781
## -----------------------------------------------------------------
## Tree 2 Rule 193 Node 377 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator <= 0.611352151120495
## 11: RMD_Year > 0.927424794280318
## 12: RMD_R10_Denominator > 0.188487766678781
## -----------------------------------------------------------------
## Tree 2 Rule 194 Node 352 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator > 0.611352151120495
## 11: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 2 Rule 195 Node 378 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator > 0.611352151120495
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central")
## -----------------------------------------------------------------
## Tree 2 Rule 196 Node 379 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator <= 0.983364985539682
## 8: Source IN ("addm", "nsch", "sped")
## 9: RMD_Year > -0.421556724672872
## 10: RMD_R10_Denominator > 0.611352151120495
## 11: RMD_Year > 0.421556724672872
## 12: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 2 Rule 197 Node 256 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator > 0.983364985539682
## 8: RMD_R10_Denominator <= 1.07301875374631
## 9: RMD_Year <= 1.01173613921489
## -----------------------------------------------------------------
## Tree 2 Rule 198 Node 257 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator > 0.983364985539682
## 8: RMD_R10_Denominator <= 1.07301875374631
## 9: RMD_Year > 1.01173613921489
## -----------------------------------------------------------------
## Tree 2 Rule 199 Node 189 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator <= 1.07433094792308
## 7: RMD_R10_Denominator > 0.983364985539682
## 8: RMD_R10_Denominator > 1.07301875374631
## -----------------------------------------------------------------
## Tree 2 Rule 200 Node 89 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator <= 1.07912139528786
## 6: RMD_R10_Denominator > 1.07433094792308
## -----------------------------------------------------------------
## Tree 2 Rule 201 Node 132 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator > 1.07912139528786
## 6: RMD_R10_Denominator <= 1.10972844471238
## 7: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 2 Rule 202 Node 190 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator > 1.07912139528786
## 6: RMD_R10_Denominator <= 1.10972844471238
## 7: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.08688694686043
## -----------------------------------------------------------------
## Tree 2 Rule 203 Node 191 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator > 1.07912139528786
## 6: RMD_R10_Denominator <= 1.10972844471238
## 7: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator > 1.08688694686043
## -----------------------------------------------------------------
## Tree 2 Rule 204 Node 91 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator <= 1.12716698644192
## 5: RMD_R10_Denominator > 1.07912139528786
## 6: RMD_R10_Denominator > 1.10972844471238
## -----------------------------------------------------------------
## Tree 2 Rule 205 Node 58 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 2 Rule 206 Node 134 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year > -0.252934034803723
## 6: RMD_Year <= 0.75880210441117
## 7: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 2 Rule 207 Node 135 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year > -0.252934034803723
## 6: RMD_Year <= 0.75880210441117
## 7: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 2 Rule 208 Node 192 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year > -0.252934034803723
## 6: RMD_Year > 0.75880210441117
## 7: RMD_R10_Denominator <= 1.29834953015751
## 8: RMD_Year <= 1.26467017401862
## -----------------------------------------------------------------
## Tree 2 Rule 209 Node 193 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year > -0.252934034803723
## 6: RMD_Year > 0.75880210441117
## 7: RMD_R10_Denominator <= 1.29834953015751
## 8: RMD_Year > 1.26467017401862
## -----------------------------------------------------------------
## Tree 2 Rule 210 Node 137 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_R10_Denominator > -0.13846253975302
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## 4: RMD_R10_Denominator > 1.12716698644192
## 5: RMD_Year > -0.252934034803723
## 6: RMD_Year > 0.75880210441117
## 7: RMD_R10_Denominator > 1.29834953015751
## -----------------------------------------------------------------
## Number of rules in Tree 2: 210
## 
## Random Forest Model 3 
## 
## -------------------------------------------------------------
## Tree 3 Rule 1 Node 14 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year <= -0.337245379738298
## -----------------------------------------------------------------
## Tree 3 Rule 2 Node 132 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D3 East North Central", "D7 West South Central")
## 6: RMD_R10_Denominator <= -1.68358640477277
## 7: RMD_R10_Denominator <= -3.09098613472366
## 8: RMD_R10_Denominator <= -3.88192222564194
## -----------------------------------------------------------------
## Tree 3 Rule 3 Node 133 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D3 East North Central", "D7 West South Central")
## 6: RMD_R10_Denominator <= -1.68358640477277
## 7: RMD_R10_Denominator <= -3.09098613472366
## 8: RMD_R10_Denominator > -3.88192222564194
## -----------------------------------------------------------------
## Tree 3 Rule 4 Node 81 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D3 East North Central", "D7 West South Central")
## 6: RMD_R10_Denominator <= -1.68358640477277
## 7: RMD_R10_Denominator > -3.09098613472366
## -----------------------------------------------------------------
## Tree 3 Rule 5 Node 47 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D3 East North Central", "D7 West South Central")
## 6: RMD_R10_Denominator > -1.68358640477277
## -----------------------------------------------------------------
## Tree 3 Rule 6 Node 82 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator <= -1.89617864815561
## -----------------------------------------------------------------
## Tree 3 Rule 7 Node 134 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 3 Rule 8 Node 312 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year <= 0.337245379738298
## 10: State_Region IN ("D5 South Atlantic")
## 11: RMD_R10_Denominator <= -1.72261654953943
## -----------------------------------------------------------------
## Tree 3 Rule 9 Node 313 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year <= 0.337245379738298
## 10: State_Region IN ("D5 South Atlantic")
## 11: RMD_R10_Denominator > -1.72261654953943
## -----------------------------------------------------------------
## Tree 3 Rule 10 Node 249 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year <= 0.337245379738298
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 11 Node 250 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year > 0.337245379738298
## 10: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 12 Node 314 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year > 0.337245379738298
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator <= -1.65377309708709
## -----------------------------------------------------------------
## Tree 3 Rule 13 Node 315 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year <= 0.674490759476595
## 7: RMD_R10_Denominator > -1.89617864815561
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_Year > 0.337245379738298
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > -1.65377309708709
## -----------------------------------------------------------------
## Tree 3 Rule 14 Node 136 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator <= -3.9241512140948
## 8: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 15 Node 190 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator <= -3.9241512140948
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 3 Rule 16 Node 191 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator <= -3.9241512140948
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 17 Node 85 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 4: RMD_Year > -0.337245379738298
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator > -3.9241512140948
## -----------------------------------------------------------------
## Tree 3 Rule 18 Node 28 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year <= 0.674490759476595
## 5: RMD_Year <= -0.168622689869149
## -----------------------------------------------------------------
## Tree 3 Rule 19 Node 50 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year <= 0.674490759476595
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 3 Rule 20 Node 86 Decision Medium
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year <= 0.674490759476595
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("nsch")
## -----------------------------------------------------------------
## Tree 3 Rule 21 Node 87 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year <= 0.674490759476595
## 5: RMD_Year > -0.168622689869149
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "medi", "sped")
## -----------------------------------------------------------------
## Tree 3 Rule 22 Node 30 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year > 0.674490759476595
## 5: RMD_R10_Denominator <= -3.92026914168528
## -----------------------------------------------------------------
## Tree 3 Rule 23 Node 52 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year > 0.674490759476595
## 5: RMD_R10_Denominator > -3.92026914168528
## 6: State_Region IN ("D1 New England", "D6 East South Central")
## -----------------------------------------------------------------
## Tree 3 Rule 24 Node 88 Decision High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year > 0.674490759476595
## 5: RMD_R10_Denominator > -3.92026914168528
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator <= -3.91799939344341
## -----------------------------------------------------------------
## Tree 3 Rule 25 Node 89 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year <= 1.34898151895319
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D9 Pacific")
## 4: RMD_Year > 0.674490759476595
## 5: RMD_R10_Denominator > -3.92026914168528
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -3.91799939344341
## -----------------------------------------------------------------
## Tree 3 Rule 26 Node 5 Decision Very High
##  
## 1: Source IN ("addm", "nsch")
## 2: RMD_Year > 1.34898151895319
## -----------------------------------------------------------------
## Tree 3 Rule 27 Node 138 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator <= -1.45662710860195
## -----------------------------------------------------------------
## Tree 3 Rule 28 Node 374 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator > -1.45662710860195
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_R10_Denominator <= -1.15540171070342
## 11: RMD_Year <= -1.09604748414947
## 12: RMD_R10_Denominator <= -1.31973466887635
## -----------------------------------------------------------------
## Tree 3 Rule 29 Node 375 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator > -1.45662710860195
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_R10_Denominator <= -1.15540171070342
## 11: RMD_Year <= -1.09604748414947
## 12: RMD_R10_Denominator > -1.31973466887635
## -----------------------------------------------------------------
## Tree 3 Rule 30 Node 317 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator > -1.45662710860195
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_R10_Denominator <= -1.15540171070342
## 11: RMD_Year > -1.09604748414947
## -----------------------------------------------------------------
## Tree 3 Rule 31 Node 253 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator > -1.45662710860195
## 9: RMD_Year <= -0.927424794280318
## 10: RMD_R10_Denominator > -1.15540171070342
## -----------------------------------------------------------------
## Tree 3 Rule 32 Node 193 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator <= -1.06926794280783
## 8: RMD_R10_Denominator > -1.45662710860195
## 9: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 3 Rule 33 Node 194 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator > -1.06926794280783
## 8: State_Region IN ("D1 New England")
## 9: RMD_R10_Denominator <= -0.783095360058372
## -----------------------------------------------------------------
## Tree 3 Rule 34 Node 195 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator > -1.06926794280783
## 8: State_Region IN ("D1 New England")
## 9: RMD_R10_Denominator > -0.783095360058372
## -----------------------------------------------------------------
## Tree 3 Rule 35 Node 141 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year <= -0.252934034803723
## 7: RMD_R10_Denominator > -1.06926794280783
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 36 Node 92 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year > -0.252934034803723
## 7: RMD_R10_Denominator <= -0.772464534063204
## -----------------------------------------------------------------
## Tree 3 Rule 37 Node 93 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D1 New England", "D3 East North Central", "D7 West South Central")
## 6: RMD_Year > -0.252934034803723
## 7: RMD_R10_Denominator > -0.772464534063204
## -----------------------------------------------------------------
## Tree 3 Rule 38 Node 254 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator <= -1.00768203719678
## 10: RMD_R10_Denominator <= -1.89255201175082
## -----------------------------------------------------------------
## Tree 3 Rule 39 Node 318 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator <= -1.00768203719678
## 10: RMD_R10_Denominator > -1.89255201175082
## 11: RMD_R10_Denominator <= -1.19386650427559
## -----------------------------------------------------------------
## Tree 3 Rule 40 Node 376 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator <= -1.00768203719678
## 10: RMD_R10_Denominator > -1.89255201175082
## 11: RMD_R10_Denominator > -1.19386650427559
## 12: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 3 Rule 41 Node 377 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator <= -1.00768203719678
## 10: RMD_R10_Denominator > -1.89255201175082
## 11: RMD_R10_Denominator > -1.19386650427559
## 12: RMD_Year > -1.09604748414947
## -----------------------------------------------------------------
## Tree 3 Rule 42 Node 320 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator > -1.00768203719678
## 10: RMD_Year <= -0.590179414542021
## 11: RMD_R10_Denominator <= -0.827898479986794
## -----------------------------------------------------------------
## Tree 3 Rule 43 Node 321 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator > -1.00768203719678
## 10: RMD_Year <= -0.590179414542021
## 11: RMD_R10_Denominator > -0.827898479986794
## -----------------------------------------------------------------
## Tree 3 Rule 44 Node 257 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year <= -0.252934034803723
## 9: RMD_R10_Denominator > -1.00768203719678
## 10: RMD_Year > -0.590179414542021
## -----------------------------------------------------------------
## Tree 3 Rule 45 Node 143 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## 8: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 46 Node 322 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= -0.590179414542021
## 9: RMD_Year <= -0.927424794280318
## 10: State_Region IN ("D5 South Atlantic")
## 11: RMD_R10_Denominator <= -1.03325158317421
## -----------------------------------------------------------------
## Tree 3 Rule 47 Node 323 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= -0.590179414542021
## 9: RMD_Year <= -0.927424794280318
## 10: State_Region IN ("D5 South Atlantic")
## 11: RMD_R10_Denominator > -1.03325158317421
## -----------------------------------------------------------------
## Tree 3 Rule 48 Node 259 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= -0.590179414542021
## 9: RMD_Year <= -0.927424794280318
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 49 Node 199 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year <= -0.590179414542021
## 9: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 3 Rule 50 Node 260 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator <= -1.64711081806901
## -----------------------------------------------------------------
## Tree 3 Rule 51 Node 324 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator > -1.64711081806901
## 11: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 52 Node 378 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator > -1.64711081806901
## 11: RMD_Year > -0.421556724672872
## 12: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 53 Node 379 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator > -1.64711081806901
## 11: RMD_Year > -0.421556724672872
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 54 Node 326 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year > -0.252934034803723
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 55 Node 327 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year > -0.252934034803723
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 56 Node 263 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_Year > -0.590179414542021
## 9: RMD_Year > -0.252934034803723
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 57 Node 96 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > -0.713275092477206
## 7: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 3 Rule 58 Node 146 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_R10_Denominator <= -0.628764324475382
## -----------------------------------------------------------------
## Tree 3 Rule 59 Node 264 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_R10_Denominator > -0.628764324475382
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator <= -0.486847641829088
## -----------------------------------------------------------------
## Tree 3 Rule 60 Node 265 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_R10_Denominator > -0.628764324475382
## 9: RMD_Year <= -0.252934034803723
## 10: RMD_R10_Denominator > -0.486847641829088
## -----------------------------------------------------------------
## Tree 3 Rule 61 Node 203 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("medi")
## 5: State_Region IN ("D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > -0.713275092477206
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 8: RMD_R10_Denominator > -0.628764324475382
## 9: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 62 Node 58 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("addm", "nsch", "sped")
## 5: State_Region IN ("D1 New England", "D5 South Atlantic")
## 6: RMD_R10_Denominator <= -0.826971596953783
## -----------------------------------------------------------------
## Tree 3 Rule 63 Node 98 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("addm", "nsch", "sped")
## 5: State_Region IN ("D1 New England", "D5 South Atlantic")
## 6: RMD_R10_Denominator > -0.826971596953783
## 7: RMD_R10_Denominator <= -0.66046296250219
## -----------------------------------------------------------------
## Tree 3 Rule 64 Node 148 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("addm", "nsch", "sped")
## 5: State_Region IN ("D1 New England", "D5 South Atlantic")
## 6: RMD_R10_Denominator > -0.826971596953783
## 7: RMD_R10_Denominator > -0.66046296250219
## 8: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 65 Node 149 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("addm", "nsch", "sped")
## 5: State_Region IN ("D1 New England", "D5 South Atlantic")
## 6: RMD_R10_Denominator > -0.826971596953783
## 7: RMD_R10_Denominator > -0.66046296250219
## 8: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 66 Node 35 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator <= -0.341653340906377
## 4: Source IN ("addm", "nsch", "sped")
## 5: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 67 Node 204 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D3 East North Central")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.53409587956303
## 8: RMD_Year <= -0.927424794280318
## 9: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 3 Rule 68 Node 205 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D3 East North Central")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.53409587956303
## 8: RMD_Year <= -0.927424794280318
## 9: RMD_Year > -1.09604748414947
## -----------------------------------------------------------------
## Tree 3 Rule 69 Node 151 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D3 East North Central")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.53409587956303
## 8: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 3 Rule 70 Node 101 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D3 East North Central")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > 0.53409587956303
## -----------------------------------------------------------------
## Tree 3 Rule 71 Node 61 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D3 East North Central")
## 6: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 3 Rule 72 Node 266 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year <= -0.590179414542021
## 8: RMD_R10_Denominator <= 0.5225287277224
## 9: State_Region IN ("D2 Middle Atlantic")
## 10: RMD_R10_Denominator <= 0.361313015791588
## -----------------------------------------------------------------
## Tree 3 Rule 73 Node 267 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year <= -0.590179414542021
## 8: RMD_R10_Denominator <= 0.5225287277224
## 9: State_Region IN ("D2 Middle Atlantic")
## 10: RMD_R10_Denominator > 0.361313015791588
## -----------------------------------------------------------------
## Tree 3 Rule 74 Node 207 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year <= -0.590179414542021
## 8: RMD_R10_Denominator <= 0.5225287277224
## 9: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 75 Node 153 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year <= -0.590179414542021
## 8: RMD_R10_Denominator > 0.5225287277224
## -----------------------------------------------------------------
## Tree 3 Rule 76 Node 268 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator <= 0.341010500000334
## 10: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 77 Node 328 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator <= 0.341010500000334
## 10: RMD_Year > -0.421556724672872
## 11: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 78 Node 329 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator <= 0.341010500000334
## 10: RMD_Year > -0.421556724672872
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 79 Node 270 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator > 0.341010500000334
## 10: State_Region IN ("D2 Middle Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 80 Node 330 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator > 0.341010500000334
## 10: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= -0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 81 Node 331 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("medi")
## 9: RMD_R10_Denominator > 0.341010500000334
## 10: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > -0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 82 Node 332 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_R10_Denominator <= 0.35798099717298
## -----------------------------------------------------------------
## Tree 3 Rule 83 Node 333 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 10: State_Region IN ("D4 West North Central")
## 11: RMD_R10_Denominator > 0.35798099717298
## -----------------------------------------------------------------
## Tree 3 Rule 84 Node 334 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator <= 0.497060978708414
## -----------------------------------------------------------------
## Tree 3 Rule 85 Node 335 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.497060978708414
## -----------------------------------------------------------------
## Tree 3 Rule 86 Node 211 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator <= 0.575873953972518
## 7: RMD_Year > -0.590179414542021
## 8: Source IN ("addm", "nsch", "sped")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 87 Node 63 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year <= -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 6: RMD_R10_Denominator > 0.575873953972518
## -----------------------------------------------------------------
## Tree 3 Rule 88 Node 336 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.0138489521079779
## 9: RMD_R10_Denominator <= -0.0598664467463477
## 10: Source IN ("medi")
## 11: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 89 Node 380 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.0138489521079779
## 9: RMD_R10_Denominator <= -0.0598664467463477
## 10: Source IN ("medi")
## 11: RMD_Year > -0.0843113449345744
## 12: RMD_R10_Denominator <= -0.22860174121906
## -----------------------------------------------------------------
## Tree 3 Rule 90 Node 381 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.0138489521079779
## 9: RMD_R10_Denominator <= -0.0598664467463477
## 10: Source IN ("medi")
## 11: RMD_Year > -0.0843113449345744
## 12: RMD_R10_Denominator > -0.22860174121906
## -----------------------------------------------------------------
## Tree 3 Rule 91 Node 275 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.0138489521079779
## 9: RMD_R10_Denominator <= -0.0598664467463477
## 10: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 3 Rule 92 Node 213 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.0138489521079779
## 9: RMD_R10_Denominator > -0.0598664467463477
## -----------------------------------------------------------------
## Tree 3 Rule 93 Node 157 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator > 0.0138489521079779
## -----------------------------------------------------------------
## Tree 3 Rule 94 Node 105 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= 0.534092648337551
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 95 Node 158 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > 0.534092648337551
## 7: RMD_R10_Denominator <= 0.63221324221725
## 8: RMD_R10_Denominator <= 0.564198902833404
## -----------------------------------------------------------------
## Tree 3 Rule 96 Node 159 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > 0.534092648337551
## 7: RMD_R10_Denominator <= 0.63221324221725
## 8: RMD_R10_Denominator > 0.564198902833404
## -----------------------------------------------------------------
## Tree 3 Rule 97 Node 160 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > 0.534092648337551
## 7: RMD_R10_Denominator > 0.63221324221725
## 8: RMD_R10_Denominator <= 0.831862381168912
## -----------------------------------------------------------------
## Tree 3 Rule 98 Node 214 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > 0.534092648337551
## 7: RMD_R10_Denominator > 0.63221324221725
## 8: RMD_R10_Denominator > 0.831862381168912
## 9: RMD_R10_Denominator <= 1.00557508495561
## -----------------------------------------------------------------
## Tree 3 Rule 99 Node 215 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > 0.534092648337551
## 7: RMD_R10_Denominator > 0.63221324221725
## 8: RMD_R10_Denominator > 0.831862381168912
## 9: RMD_R10_Denominator > 1.00557508495561
## -----------------------------------------------------------------
## Tree 3 Rule 100 Node 162 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.181810386494299
## 8: RMD_R10_Denominator <= 0.0122021076862904
## -----------------------------------------------------------------
## Tree 3 Rule 101 Node 216 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.181810386494299
## 8: RMD_R10_Denominator > 0.0122021076862904
## 9: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 102 Node 217 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator <= 0.181810386494299
## 8: RMD_R10_Denominator > 0.0122021076862904
## 9: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 103 Node 109 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("medi")
## 7: RMD_R10_Denominator > 0.181810386494299
## -----------------------------------------------------------------
## Tree 3 Rule 104 Node 110 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("addm", "nsch", "sped")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central")
## -----------------------------------------------------------------
## Tree 3 Rule 105 Node 164 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("addm", "nsch", "sped")
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 106 Node 165 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year <= 0.0843113449345744
## 3: RMD_R10_Denominator > -0.341653340906377
## 4: RMD_Year > -0.252934034803723
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D9 Pacific")
## 6: Source IN ("addm", "nsch", "sped")
## 7: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 3 Rule 107 Node 112 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator <= -0.508863201282255
## 6: RMD_R10_Denominator <= -0.894782439438856
## 7: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 3 Rule 108 Node 113 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator <= -0.508863201282255
## 6: RMD_R10_Denominator <= -0.894782439438856
## 7: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 3 Rule 109 Node 69 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator <= -0.508863201282255
## 6: RMD_R10_Denominator > -0.894782439438856
## -----------------------------------------------------------------
## Tree 3 Rule 110 Node 70 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator > -0.508863201282255
## 6: RMD_R10_Denominator <= -0.0986104269827017
## -----------------------------------------------------------------
## Tree 3 Rule 111 Node 114 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator > -0.508863201282255
## 6: RMD_R10_Denominator > -0.0986104269827017
## 7: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 112 Node 115 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year <= 0.927424794280318
## 5: RMD_R10_Denominator > -0.508863201282255
## 6: RMD_R10_Denominator > -0.0986104269827017
## 7: RMD_Year > 0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 113 Node 23 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D1 New England")
## 4: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 3 Rule 114 Node 276 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -1.21720714646834
## 8: RMD_Year <= 0.421556724672872
## 9: RMD_Year <= 0.252934034803723
## 10: RMD_R10_Denominator <= -1.64947623351459
## -----------------------------------------------------------------
## Tree 3 Rule 115 Node 277 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -1.21720714646834
## 8: RMD_Year <= 0.421556724672872
## 9: RMD_Year <= 0.252934034803723
## 10: RMD_R10_Denominator > -1.64947623351459
## -----------------------------------------------------------------
## Tree 3 Rule 116 Node 219 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -1.21720714646834
## 8: RMD_Year <= 0.421556724672872
## 9: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 117 Node 220 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -1.21720714646834
## 8: RMD_Year > 0.421556724672872
## 9: RMD_R10_Denominator <= -1.47256298451448
## -----------------------------------------------------------------
## Tree 3 Rule 118 Node 221 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -1.21720714646834
## 8: RMD_Year > 0.421556724672872
## 9: RMD_R10_Denominator > -1.47256298451448
## -----------------------------------------------------------------
## Tree 3 Rule 119 Node 408 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D6 East South Central")
## 12: RMD_R10_Denominator <= -0.0513934211344727
## 13: RMD_R10_Denominator <= -0.13933149935511
## -----------------------------------------------------------------
## Tree 3 Rule 120 Node 409 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D6 East South Central")
## 12: RMD_R10_Denominator <= -0.0513934211344727
## 13: RMD_R10_Denominator > -0.13933149935511
## -----------------------------------------------------------------
## Tree 3 Rule 121 Node 383 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D6 East South Central")
## 12: RMD_R10_Denominator > -0.0513934211344727
## -----------------------------------------------------------------
## Tree 3 Rule 122 Node 384 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: State_Region IN ("D7 West South Central")
## -----------------------------------------------------------------
## Tree 3 Rule 123 Node 410 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator <= 0.0668008554250329
## -----------------------------------------------------------------
## Tree 3 Rule 124 Node 411 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator <= 0.266710084156614
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator > 0.0668008554250329
## -----------------------------------------------------------------
## Tree 3 Rule 125 Node 279 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator <= 1.49656861320311
## 10: RMD_R10_Denominator > 0.266710084156614
## -----------------------------------------------------------------
## Tree 3 Rule 126 Node 223 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year <= 0.252934034803723
## 9: RMD_R10_Denominator > 1.49656861320311
## -----------------------------------------------------------------
## Tree 3 Rule 127 Node 280 Decision Very High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator <= -0.0768653672926222
## 10: RMD_R10_Denominator <= -0.805290034100144
## -----------------------------------------------------------------
## Tree 3 Rule 128 Node 340 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator <= -0.0768653672926222
## 10: RMD_R10_Denominator > -0.805290034100144
## 11: RMD_Year <= 0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 129 Node 341 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator <= -0.0768653672926222
## 10: RMD_R10_Denominator > -0.805290034100144
## 11: RMD_Year > 0.421556724672872
## -----------------------------------------------------------------
## Tree 3 Rule 130 Node 282 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator > -0.0768653672926222
## 10: RMD_R10_Denominator <= 0.150754457672401
## -----------------------------------------------------------------
## Tree 3 Rule 131 Node 386 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator > -0.0768653672926222
## 10: RMD_R10_Denominator > 0.150754457672401
## 11: State_Region IN ("D6 East South Central", "D7 West South Central")
## 12: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 3 Rule 132 Node 412 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator > -0.0768653672926222
## 10: RMD_R10_Denominator > 0.150754457672401
## 11: State_Region IN ("D6 East South Central", "D7 West South Central")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator <= 0.323782155885225
## -----------------------------------------------------------------
## Tree 3 Rule 133 Node 413 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator > -0.0768653672926222
## 10: RMD_R10_Denominator > 0.150754457672401
## 11: State_Region IN ("D6 East South Central", "D7 West South Central")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator > 0.323782155885225
## -----------------------------------------------------------------
## Tree 3 Rule 134 Node 343 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -1.21720714646834
## 8: RMD_Year > 0.252934034803723
## 9: RMD_R10_Denominator > -0.0768653672926222
## 10: RMD_R10_Denominator > 0.150754457672401
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 135 Node 284 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator <= -1.32016482672945
## 10: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 136 Node 285 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator <= -1.32016482672945
## 10: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 137 Node 227 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic")
## 9: RMD_R10_Denominator > -1.32016482672945
## -----------------------------------------------------------------
## Tree 3 Rule 138 Node 171 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -1.21301203353821
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 139 Node 388 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year <= 0.252934034803723
## 11: State_Region IN ("D4 West North Central")
## 12: RMD_R10_Denominator <= -0.379052413340944
## -----------------------------------------------------------------
## Tree 3 Rule 140 Node 414 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year <= 0.252934034803723
## 11: State_Region IN ("D4 West North Central")
## 12: RMD_R10_Denominator > -0.379052413340944
## 13: RMD_R10_Denominator <= -0.050466239798411
## -----------------------------------------------------------------
## Tree 3 Rule 141 Node 415 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year <= 0.252934034803723
## 11: State_Region IN ("D4 West North Central")
## 12: RMD_R10_Denominator > -0.379052413340944
## 13: RMD_R10_Denominator > -0.050466239798411
## -----------------------------------------------------------------
## Tree 3 Rule 142 Node 390 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year <= 0.252934034803723
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_R10_Denominator <= 0.489990887764785
## -----------------------------------------------------------------
## Tree 3 Rule 143 Node 391 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year <= 0.252934034803723
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: RMD_R10_Denominator > 0.489990887764785
## -----------------------------------------------------------------
## Tree 3 Rule 144 Node 346 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year > 0.252934034803723
## 11: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 145 Node 347 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("medi")
## 10: RMD_Year > 0.252934034803723
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 146 Node 348 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.494795267977915
## 11: RMD_R10_Denominator <= -0.411388347991879
## -----------------------------------------------------------------
## Tree 3 Rule 147 Node 392 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.494795267977915
## 11: RMD_R10_Denominator > -0.411388347991879
## 12: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 3 Rule 148 Node 428 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.494795267977915
## 11: RMD_R10_Denominator > -0.411388347991879
## 12: RMD_Year > 0.252934034803723
## 13: State_Region IN ("D4 West North Central")
## 14: RMD_R10_Denominator <= -0.0393575706673743
## -----------------------------------------------------------------
## Tree 3 Rule 149 Node 429 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.494795267977915
## 11: RMD_R10_Denominator > -0.411388347991879
## 12: RMD_Year > 0.252934034803723
## 13: State_Region IN ("D4 West North Central")
## 14: RMD_R10_Denominator > -0.0393575706673743
## -----------------------------------------------------------------
## Tree 3 Rule 150 Node 417 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.494795267977915
## 11: RMD_R10_Denominator > -0.411388347991879
## 12: RMD_Year > 0.252934034803723
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 151 Node 350 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.494795267977915
## 11: RMD_R10_Denominator <= 1.3003793245289
## -----------------------------------------------------------------
## Tree 3 Rule 152 Node 394 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.494795267977915
## 11: RMD_R10_Denominator > 1.3003793245289
## 12: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 153 Node 395 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year <= 0.421556724672872
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.494795267977915
## 11: RMD_R10_Denominator > 1.3003793245289
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 154 Node 290 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 10: RMD_R10_Denominator <= 0.640942463794896
## -----------------------------------------------------------------
## Tree 3 Rule 155 Node 352 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 10: RMD_R10_Denominator > 0.640942463794896
## 11: RMD_R10_Denominator <= 0.724641627495096
## -----------------------------------------------------------------
## Tree 3 Rule 156 Node 353 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 10: RMD_R10_Denominator > 0.640942463794896
## 11: RMD_R10_Denominator > 0.724641627495096
## -----------------------------------------------------------------
## Tree 3 Rule 157 Node 418 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator <= 1.49107842140064
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator <= 0.788976469735384
## -----------------------------------------------------------------
## Tree 3 Rule 158 Node 430 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator <= 1.49107842140064
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator > 0.788976469735384
## 14: RMD_R10_Denominator <= 1.05214853615965
## -----------------------------------------------------------------
## Tree 3 Rule 159 Node 436 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator <= 1.49107842140064
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator > 0.788976469735384
## 14: RMD_R10_Denominator > 1.05214853615965
## 15: RMD_R10_Denominator <= 1.26310521960351
## -----------------------------------------------------------------
## Tree 3 Rule 160 Node 437 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator <= 1.49107842140064
## 12: State_Region IN ("D2 Middle Atlantic")
## 13: RMD_R10_Denominator > 0.788976469735384
## 14: RMD_R10_Denominator > 1.05214853615965
## 15: RMD_R10_Denominator > 1.26310521960351
## -----------------------------------------------------------------
## Tree 3 Rule 161 Node 397 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator <= 1.49107842140064
## 12: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 162 Node 355 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 1.79857542325958
## 11: RMD_R10_Denominator > 1.49107842140064
## -----------------------------------------------------------------
## Tree 3 Rule 163 Node 293 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year <= 0.590179414542021
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -1.21301203353821
## 8: RMD_Year > 0.421556724672872
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 1.79857542325958
## -----------------------------------------------------------------
## Tree 3 Rule 164 Node 356 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.268257701940531
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.174535140506537
## 11: RMD_R10_Denominator <= -0.355533852223818
## -----------------------------------------------------------------
## Tree 3 Rule 165 Node 357 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.268257701940531
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator <= 0.174535140506537
## 11: RMD_R10_Denominator > -0.355533852223818
## -----------------------------------------------------------------
## Tree 3 Rule 166 Node 295 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.268257701940531
## 9: RMD_Year <= 0.75880210441117
## 10: RMD_R10_Denominator > 0.174535140506537
## -----------------------------------------------------------------
## Tree 3 Rule 167 Node 233 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator <= 0.268257701940531
## 9: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 3 Rule 168 Node 175 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D6 East South Central")
## 8: RMD_R10_Denominator > 0.268257701940531
## -----------------------------------------------------------------
## Tree 3 Rule 169 Node 296 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator <= -1.21107183932151
## 10: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 3 Rule 170 Node 358 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator <= -1.21107183932151
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator <= -1.42227669777106
## -----------------------------------------------------------------
## Tree 3 Rule 171 Node 398 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator <= -1.21107183932151
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > -1.42227669777106
## 12: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 3 Rule 172 Node 420 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator <= -1.21107183932151
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > -1.42227669777106
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_R10_Denominator <= -1.22190757192299
## -----------------------------------------------------------------
## Tree 3 Rule 173 Node 421 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator <= -1.21107183932151
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > -1.42227669777106
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_R10_Denominator > -1.22190757192299
## -----------------------------------------------------------------
## Tree 3 Rule 174 Node 360 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator <= -0.664797788210082
## 11: RMD_R10_Denominator <= -1.03849450436078
## -----------------------------------------------------------------
## Tree 3 Rule 175 Node 361 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator <= -0.664797788210082
## 11: RMD_R10_Denominator > -1.03849450436078
## -----------------------------------------------------------------
## Tree 3 Rule 176 Node 422 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator <= -0.0752981209272314
## 12: RMD_R10_Denominator <= -0.491617210761592
## 13: RMD_R10_Denominator <= -0.571021771333372
## -----------------------------------------------------------------
## Tree 3 Rule 177 Node 423 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator <= -0.0752981209272314
## 12: RMD_R10_Denominator <= -0.491617210761592
## 13: RMD_R10_Denominator > -0.571021771333372
## -----------------------------------------------------------------
## Tree 3 Rule 178 Node 401 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator <= -0.0752981209272314
## 12: RMD_R10_Denominator > -0.491617210761592
## -----------------------------------------------------------------
## Tree 3 Rule 179 Node 424 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D4 West North Central", "D8 Mountain")
## 13: RMD_R10_Denominator <= -0.0438621612118009
## -----------------------------------------------------------------
## Tree 3 Rule 180 Node 425 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D4 West North Central", "D8 Mountain")
## 13: RMD_R10_Denominator > -0.0438621612118009
## -----------------------------------------------------------------
## Tree 3 Rule 181 Node 432 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_Year <= 0.75880210441117
## 14: RMD_R10_Denominator <= 0.444272042570772
## -----------------------------------------------------------------
## Tree 3 Rule 182 Node 433 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_Year <= 0.75880210441117
## 14: RMD_R10_Denominator > 0.444272042570772
## -----------------------------------------------------------------
## Tree 3 Rule 183 Node 434 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_Year > 0.75880210441117
## 14: RMD_R10_Denominator <= 0.500634372377747
## -----------------------------------------------------------------
## Tree 3 Rule 184 Node 435 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 1.22162150945154
## 9: RMD_R10_Denominator > -1.21107183932151
## 10: RMD_R10_Denominator > -0.664797788210082
## 11: RMD_R10_Denominator > -0.0752981209272314
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 13: RMD_Year > 0.75880210441117
## 14: RMD_R10_Denominator > 0.500634372377747
## -----------------------------------------------------------------
## Tree 3 Rule 185 Node 177 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("medi")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator > 1.22162150945154
## -----------------------------------------------------------------
## Tree 3 Rule 186 Node 364 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator <= 0.210097401460511
## 10: RMD_R10_Denominator <= 0.137088926980082
## 11: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 3 Rule 187 Node 365 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator <= 0.210097401460511
## 10: RMD_R10_Denominator <= 0.137088926980082
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 188 Node 301 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator <= 0.210097401460511
## 10: RMD_R10_Denominator > 0.137088926980082
## -----------------------------------------------------------------
## Tree 3 Rule 189 Node 302 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator > 0.210097401460511
## 10: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 3 Rule 190 Node 404 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator > 0.210097401460511
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D8 Mountain", "D9 Pacific")
## 11: State_Region IN ("D3 East North Central")
## 12: RMD_R10_Denominator <= 0.865132582448638
## -----------------------------------------------------------------
## Tree 3 Rule 191 Node 405 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator > 0.210097401460511
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D8 Mountain", "D9 Pacific")
## 11: State_Region IN ("D3 East North Central")
## 12: RMD_R10_Denominator > 0.865132582448638
## -----------------------------------------------------------------
## Tree 3 Rule 192 Node 367 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year <= 0.75880210441117
## 9: RMD_R10_Denominator > 0.210097401460511
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D8 Mountain", "D9 Pacific")
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 193 Node 238 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year > 0.75880210441117
## 9: RMD_R10_Denominator <= 0.79899349516512
## -----------------------------------------------------------------
## Tree 3 Rule 194 Node 304 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year > 0.75880210441117
## 9: RMD_R10_Denominator > 0.79899349516512
## 10: State_Region IN ("D3 East North Central", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 3 Rule 195 Node 368 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year > 0.75880210441117
## 9: RMD_R10_Denominator > 0.79899349516512
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator <= 1.25231084170347
## -----------------------------------------------------------------
## Tree 3 Rule 196 Node 369 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.927424794280318
## 8: RMD_Year > 0.75880210441117
## 9: RMD_R10_Denominator > 0.79899349516512
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_R10_Denominator > 1.25231084170347
## -----------------------------------------------------------------
## Tree 3 Rule 197 Node 180 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator <= 0.512138415096574
## -----------------------------------------------------------------
## Tree 3 Rule 198 Node 406 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator > 0.512138415096574
## 9: RMD_R10_Denominator <= 1.93530277104931
## 10: RMD_R10_Denominator <= 1.46461330873921
## 11: RMD_R10_Denominator <= 1.07476024961469
## 12: State_Region IN ("D2 Middle Atlantic", "D3 East North Central")
## -----------------------------------------------------------------
## Tree 3 Rule 199 Node 407 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator > 0.512138415096574
## 9: RMD_R10_Denominator <= 1.93530277104931
## 10: RMD_R10_Denominator <= 1.46461330873921
## 11: RMD_R10_Denominator <= 1.07476024961469
## 12: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 200 Node 371 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator > 0.512138415096574
## 9: RMD_R10_Denominator <= 1.93530277104931
## 10: RMD_R10_Denominator <= 1.46461330873921
## 11: RMD_R10_Denominator > 1.07476024961469
## -----------------------------------------------------------------
## Tree 3 Rule 201 Node 307 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator > 0.512138415096574
## 9: RMD_R10_Denominator <= 1.93530277104931
## 10: RMD_R10_Denominator > 1.46461330873921
## -----------------------------------------------------------------
## Tree 3 Rule 202 Node 241 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year <= 1.09604748414947
## 5: RMD_Year > 0.590179414542021
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.927424794280318
## 8: RMD_R10_Denominator > 0.512138415096574
## 9: RMD_R10_Denominator > 1.93530277104931
## -----------------------------------------------------------------
## Tree 3 Rule 203 Node 124 Decision Low
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator <= -0.454967416010709
## -----------------------------------------------------------------
## Tree 3 Rule 204 Node 125 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: RMD_R10_Denominator > -0.454967416010709
## -----------------------------------------------------------------
## Tree 3 Rule 205 Node 182 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D4 West North Central")
## 8: RMD_Year <= 1.26467017401862
## -----------------------------------------------------------------
## Tree 3 Rule 206 Node 242 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D4 West North Central")
## 8: RMD_Year > 1.26467017401862
## 9: RMD_R10_Denominator <= -0.476178403465712
## -----------------------------------------------------------------
## Tree 3 Rule 207 Node 243 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D4 West North Central")
## 8: RMD_Year > 1.26467017401862
## 9: RMD_R10_Denominator > -0.476178403465712
## -----------------------------------------------------------------
## Tree 3 Rule 208 Node 372 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.386400186003015
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator <= -0.519259141453346
## 11: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 209 Node 373 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.386400186003015
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator <= -0.519259141453346
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 210 Node 309 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.386400186003015
## 9: RMD_Year <= 1.43329286388776
## 10: RMD_R10_Denominator > -0.519259141453346
## -----------------------------------------------------------------
## Tree 3 Rule 211 Node 245 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.386400186003015
## 9: RMD_Year > 1.43329286388776
## -----------------------------------------------------------------
## Tree 3 Rule 212 Node 185 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator <= 0.51868583993163
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator > 0.386400186003015
## -----------------------------------------------------------------
## Tree 3 Rule 213 Node 128 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator <= 0.69785130646179
## 7: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 3 Rule 214 Node 129 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator <= 0.69785130646179
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 3 Rule 215 Node 130 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator > 0.69785130646179
## 7: RMD_R10_Denominator <= 1.08010596289803
## -----------------------------------------------------------------
## Tree 3 Rule 216 Node 186 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator > 0.69785130646179
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_R10_Denominator <= 1.08555682834203
## -----------------------------------------------------------------
## Tree 3 Rule 217 Node 246 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator > 0.69785130646179
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_R10_Denominator > 1.08555682834203
## 9: RMD_R10_Denominator <= 1.65261073887043
## -----------------------------------------------------------------
## Tree 3 Rule 218 Node 310 Decision Medium
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator > 0.69785130646179
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_R10_Denominator > 1.08555682834203
## 9: RMD_R10_Denominator > 1.65261073887043
## 10: RMD_R10_Denominator <= 1.94635743582358
## -----------------------------------------------------------------
## Tree 3 Rule 219 Node 311 Decision High
##  
## 1: Source IN ("medi", "sped")
## 2: RMD_Year > 0.0843113449345744
## 3: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: RMD_Year > 1.09604748414947
## 5: RMD_R10_Denominator > 0.51868583993163
## 6: RMD_R10_Denominator > 0.69785130646179
## 7: RMD_R10_Denominator > 1.08010596289803
## 8: RMD_R10_Denominator > 1.08555682834203
## 9: RMD_R10_Denominator > 1.65261073887043
## 10: RMD_R10_Denominator > 1.94635743582358
## -----------------------------------------------------------------
## Number of rules in Tree 3: 219
<h3>
Multi-Class Model: Support Vector Machines (SVM)
</h3>

if(!require(kernlab)){install.packages("kernlab")}
## Loading required package: kernlab
## 
## Attaching package: 'kernlab'
## The following object is masked from 'package:CircStats':
## 
##     rvm
## The following object is masked from 'package:ggplot2':
## 
##     alpha
library('kernlab')
#=======================================================================
# Rattle timestamp: 2019-12-23 16:17:34 x86_64-pc-linux-gnu 

# Support vector machine. 

# The 'kernlab' package provides the 'ksvm' function.

library(kernlab, quietly=TRUE)

# Build a Support Vector Machine model.

set.seed(crv$seed)
crs$ksvm <- ksvm(as.factor(Prevalence_Risk4) ~ .,
      data=crs$dataset[crs$train,c(crs$input, crs$target)],
      kernel="rbfdot",
      prob.model=TRUE)

# Generate a textual view of the SVM model.

crs$ksvm
## Support Vector Machine object of class "ksvm" 
## 
## SV type: C-svc  (classification) 
##  parameter : cost C = 1 
## 
## Gaussian Radial Basis kernel function. 
##  Hyperparameter : sigma =  0.264793394699108 
## 
## Number of Support Vectors : 775 
## 
## Objective Function Value : -122.8819 -260.3999 -64.3957 -377.883 -21.0568 -30.3267 
## Training error : 0.228041 
## Probability model included.
# Time taken: 0.40 secs
<h3>
Multi-Class Model: Multinomial Logistic Regression
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 16:13:19 x86_64-pc-linux-gnu 

# Regression model 

# Build a multinomial model using the nnet package.

library(nnet, quietly=TRUE)

# Summarise multinomial model using Anova from the car package.

library(car, quietly=TRUE)
## Registered S3 methods overwritten by 'car':
##   method                          from
##   influence.merMod                lme4
##   cooks.distance.influence.merMod lme4
##   dfbeta.influence.merMod         lme4
##   dfbetas.influence.merMod        lme4
## 
## Attaching package: 'car'
## The following object is masked from 'package:boot':
## 
##     logit
## The following object is masked from 'package:fBasics':
## 
##     densityPlot
# Build a Regression model.

crs$glm <- multinom(Prevalence_Risk4 ~ ., data=crs$dataset[crs$train,c(crs$input, crs$target)], trace=FALSE, maxit=1000)

# Generate a textual view of the Linear model.

rattle.print.summary.multinom(summary(crs$glm,
                              Wald.ratios=TRUE))
## Call:
## multinom(formula = Prevalence_Risk4 ~ ., data = crs$dataset[crs$train, 
##     c(crs$input, crs$target)], trace = FALSE, maxit = 1000)
## 
## n=1184
## 
## Coefficients:
##           (Intercept) Sourcemedi  Sourcensch Sourcesped
## Low         -7.613185   6.664750 -10.3505526    7.57715
## Medium      -2.609530   2.620152  -0.7744868    3.39157
## Very High   -9.457761   4.489966  -2.5620704  -12.32038
##           State_RegionD2 Middle Atlantic State_RegionD3 East North Central
## Low                             2.455462                          1.659605
## Medium                          1.908225                          2.242230
## Very High                       2.070621                          1.650636
##           State_RegionD4 West North Central State_RegionD5 South Atlantic
## Low                                2.931481                    3.22348888
## Medium                             1.732136                    2.34752178
## Very High                         -0.570721                    0.02696508
##           State_RegionD6 East South Central State_RegionD7 West South Central
## Low                                5.350321                          6.165719
## Medium                             3.470543                          4.413084
## Very High                          4.747385                        -12.369540
##           State_RegionD8 Mountain State_RegionD9 Pacific  RMD_Year
## Low                    4.41036609             3.25616127 -4.835583
## Medium                 2.63924552             2.30626004 -2.317726
## Very High             -0.06124791            -0.04362339  1.859182
##           RMD_R10_Denominator
## Low                 0.3074444
## Medium             -0.1204748
## Very High          -2.5584385
## 
## Std. Errors:
##           (Intercept) Sourcemedi   Sourcensch   Sourcesped
## Low         1.2608326  1.1611091 8.013749e-06 1.207691e+00
## Medium      0.6202386  0.4949248 7.516732e-01 5.667068e-01
## Very High   1.9852781  1.2743853 1.317997e+00 1.212326e-05
##           State_RegionD2 Middle Atlantic State_RegionD3 East North Central
## Low                            0.6525139                         0.5827186
## Medium                         0.5205660                         0.4543185
## Very High                      1.0400958                         1.0703368
##           State_RegionD4 West North Central State_RegionD5 South Atlantic
## Low                               0.4889231                     0.4924479
## Medium                            0.3898820                     0.3905864
## Very High                         0.7939857                     0.7488800
##           State_RegionD6 East South Central State_RegionD7 West South Central
## Low                               0.7383861                      8.217339e-01
## Medium                            0.6507076                      7.267081e-01
## Very High                         1.2440164                      6.831242e-06
##           State_RegionD8 Mountain State_RegionD9 Pacific  RMD_Year
## Low                     0.5160720              0.5613361 0.2914161
## Medium                  0.4193055              0.4552103 0.2431923
## Very High               0.7515523              0.8471866 0.5504168
##           RMD_R10_Denominator
## Low                 0.2009441
## Medium              0.1656867
## Very High           0.6558186
## 
## Value/SE (Wald statistics):
##           (Intercept) Sourcemedi    Sourcensch   Sourcesped
## Low         -6.038220   5.739986 -1.291599e+06  6.27408e+00
## Medium      -4.207299   5.294039 -1.030350e+00  5.98470e+00
## Very High   -4.763948   3.523240 -1.943912e+00 -1.01626e+06
##           State_RegionD2 Middle Atlantic State_RegionD3 East North Central
## Low                             3.763080                          2.848039
## Medium                          3.665673                          4.935371
## Very High                       1.990799                          1.542165
##           State_RegionD4 West North Central State_RegionD5 South Atlantic
## Low                               5.9957915                    6.54584790
## Medium                            4.4427188                    6.01024955
## Very High                        -0.7188051                    0.03600721
##           State_RegionD6 East South Central State_RegionD7 West South Central
## Low                                7.245967                      7.503304e+00
## Medium                             5.333491                      6.072705e+00
## Very High                          3.816176                     -1.810731e+06
##           State_RegionD8 Mountain State_RegionD9 Pacific   RMD_Year
## Low                     8.5460293             5.80073415 -16.593395
## Medium                  6.2943256             5.06636131  -9.530425
## Very High              -0.0814952            -0.05149206   3.377771
##           RMD_R10_Denominator
## Low                 1.5299996
## Medium             -0.7271242
## Very High          -3.9011376
## 
## Residual Deviance: 1554.522 
## AIC: 1638.522
cat(sprintf("Log likelihood: %.3f (%d df)
", logLik(crs$glm)[1], attr(logLik(crs$glm), "df")))
## Log likelihood: -777.261 (42 df)
if (is.null(crs$glm$na.action)) omitted <- TRUE else omitted <- -crs$glm$na.action
cat(sprintf("Pseudo R-Square: %.8f

",cor(apply(crs$glm$fitted.values, 1, function(x) which(x == max(x))),
as.integer(crs$dataset[crs$train,][omitted,]$Prevalence_Risk4))))
## Pseudo R-Square: 0.42805951
cat('==== ANOVA ====
')
## ==== ANOVA ====
print(Anova(crs$glm))
## Analysis of Deviance Table (Type II tests)
## 
## Response: Prevalence_Risk4
##                     LR Chisq Df Pr(>Chisq)    
## Source                114.48  9  < 2.2e-16 ***
## State_Region          200.79 24  < 2.2e-16 ***
## RMD_Year              710.89  3  < 2.2e-16 ***
## RMD_R10_Denominator    30.15  3  1.281e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
print("
")
## [1] "\n"
# Time taken: 0.37 secs
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Evaluate Model (Classification: Multi-Class)

Multi-Class Classification: Prevalence_Risk4

crs$rpart
crs$rf
crs$ksvm
crs$glm
<h3>
Rattle: Evaluate Model (Classification): Error/Confusion matrix
</h3>

crs$target
## [1] "Prevalence_Risk4"
#=======================================================================
# Rattle timestamp: 2019-12-23 16:32:12 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# Generate an Error Matrix for the Decision Tree model.

# Obtain the response from the Decision Tree model.

crs$pr <- predict(crs$rpart, newdata=crs$dataset[crs$test, c(crs$input, crs$target)],
    type="class")

# Generate the confusion matrix showing counts.

rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk4, crs$pr, count=TRUE)
##            Predicted
## Actual      High Low Medium Very High Error
##   High        23   1     19         1  47.7
##   Low          1  88     26         0  23.5
##   Medium       5  23     54         0  34.1
##   Very High    6   0      1         7  50.0
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk4, crs$pr))
##            Predicted
## Actual      High  Low Medium Very High Error
##   High       9.0  0.4    7.5       0.4  47.7
##   Low        0.4 34.5   10.2       0.0  23.5
##   Medium     2.0  9.0   21.2       0.0  34.1
##   Very High  2.4  0.0    0.4       2.7  50.0
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 32.6
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 38.825
# Generate an Error Matrix for the Random Forest model.

# Obtain the response from the Random Forest model.

crs$pr <- predict(crs$rf, newdata=na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]))

# Generate the confusion matrix showing counts.

rattle::errorMatrix(na.omit(crs$dataset[crs$test, c(crs$input, crs$target)])$Prevalence_Risk4, crs$pr, count=TRUE)
##            Predicted
## Actual      High Low Medium Very High Error
##   High        28   0     12         4  36.4
##   Low          1  97     17         0  15.7
##   Medium       5  20     57         0  30.5
##   Very High    4   1      0         9  35.7
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(na.omit(crs$dataset[crs$test, c(crs$input, crs$target)])$Prevalence_Risk4, crs$pr))
##            Predicted
## Actual      High  Low Medium Very High Error
##   High      11.0  0.0    4.7       1.6  36.4
##   Low        0.4 38.0    6.7       0.0  15.7
##   Medium     2.0  7.8   22.4       0.0  30.5
##   Very High  1.6  0.4    0.0       3.5  35.7
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 25.1
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 29.575
# Generate an Error Matrix for the SVM model.

# Obtain the response from the SVM model.

crs$pr <- kernlab::predict(crs$ksvm, newdata=na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]))

# Generate the confusion matrix showing counts.

rattle::errorMatrix(na.omit(crs$dataset[crs$test, c(crs$input, crs$target)])$Prevalence_Risk4, crs$pr, count=TRUE)
##            Predicted
## Actual      High Low Medium Very High Error
##   High        25   2     14         3  43.2
##   Low          3  94     18         0  18.3
##   Medium       6  29     47         0  42.7
##   Very High    6   0      1         7  50.0
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(na.omit(crs$dataset[crs$test, c(crs$input, crs$target)])$Prevalence_Risk4, crs$pr))
##            Predicted
## Actual      High  Low Medium Very High Error
##   High       9.8  0.8    5.5       1.2  43.2
##   Low        1.2 36.9    7.1       0.0  18.3
##   Medium     2.4 11.4   18.4       0.0  42.7
##   Very High  2.4  0.0    0.4       2.7  50.0
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 32.2
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 38.55
# Generate an Error Matrix for the Linear model.

# Obtain the response from the Linear model.

crs$pr <- predict(crs$glm, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Generate the confusion matrix showing counts.

rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk4, crs$pr, count=TRUE)
##            Predicted
## Actual      High Low Medium Very High Error
##   High        22   2     17         3  50.0
##   Low          3  97     15         0  15.7
##   Medium       8  28     46         0  43.9
##   Very High    5   0      1         8  42.9
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk4, crs$pr))
##            Predicted
## Actual      High  Low Medium Very High Error
##   High       8.6  0.8    6.7       1.2  50.0
##   Low        1.2 38.0    5.9       0.0  15.7
##   Medium     3.1 11.0   18.0       0.0  43.9
##   Very High  2.0  0.0    0.4       3.1  42.9
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 32.3
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 38.125
<h3>
Rattle: Evaluate Model (Classification): Score/Write predicted results to CSV file.
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-23 16:50:20 x86_64-pc-linux-gnu 

# Score the testing dataset. 

# Obtain probability scores for the Decision Tree model on ADV_ASD_State_R.csv [test].

crs$pr_rpart <- predict(crs$rpart, newdata=crs$dataset[crs$test, c(crs$input)],
    type="class")

# Obtain probability scores for the Random Forest model on ADV_ASD_State_R.csv [test].

crs$pr_rf <- predict(crs$rf, newdata=na.omit(crs$dataset[crs$test, c(crs$input)]))

# Obtain probability scores for the SVM model on ADV_ASD_State_R.csv [test].

crs$pr_ksvm <- kernlab::predict(crs$ksvm, newdata=na.omit(crs$dataset[crs$test, c(crs$input)]))

# Obtain probability scores for the Linear model on ADV_ASD_State_R.csv [test].

crs$pr_glm <- predict(crs$glm, newdata=crs$dataset[crs$test, c(crs$input)])

# Extract the relevant variables from the dataset.

sdata <- crs$dataset[crs$test,]

# Output the combined data.

write.csv(cbind(sdata, crs$pr_rpart, crs$pr_rf, crs$pr_ksvm, crs$pr_glm), row.names=FALSE,
          file="../reference/R rattle/ADV_ASD_State_R_test_score_all_Prevalence_Risk4.csv")

Rattle: Train Model (Classification)

Binary-Class Classification: Prevalence_Risk2

#=======================================================================
# Rattle timestamp: 2019-12-24 10:52:36 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(88)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("Source", "State_Region", "RMD_Year",
                   "RMD_R10_Denominator")

crs$numeric   <- c("RMD_Year", "RMD_R10_Denominator")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence_Risk2"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Denominator", "Prevalence", "Lower.CI", "Upper.CI", "Year", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk4", "Year_Factor", "R10_Denominator")
crs$weights   <- NULL
crs$target
## [1] "Prevalence_Risk2"
crs$input
## [1] "Source"              "State_Region"        "RMD_Year"           
## [4] "RMD_R10_Denominator"
<h3>
Binary-Class Model: Boost
</h3>

Ada Boost: Adaptive Boosting

if(!require(ada)){install.packages("ada")}
## Loading required package: ada
library('ada')
#=======================================================================
# Rattle timestamp: 2019-12-24 11:00:37 x86_64-pc-linux-gnu 

# Ada Boost 

# The `ada' package implements the boost algorithm.

# Build the Ada Boost model.

set.seed(crv$seed)
crs$ada <- ada::ada(Prevalence_Risk2 ~ .,
                    data=crs$dataset[crs$train,c(crs$input, crs$target)],
                    control=rpart::rpart.control(maxdepth=6,
                                                 cp=0.010000,
                                                 minsplit=20,
                                                 xval=10),
                    iter=50)

# Print the results of the modelling.

print(crs$ada)
## Call:
## ada(Prevalence_Risk2 ~ ., data = crs$dataset[crs$train, c(crs$input, 
##     crs$target)], control = rpart::rpart.control(maxdepth = 6, 
##     cp = 0.01, minsplit = 20, xval = 10), iter = 50)
## 
## Loss: exponential Method: discrete   Iteration: 50 
## 
## Final Confusion Matrix for Data:
##           Final Prediction
## True value High Low
##       High  618  57
##       Low    63 446
## 
## Train Error: 0.101 
## 
## Out-Of-Bag Error:  0.112  iteration= 45 
## 
## Additional Estimates of number of iterations:
## 
## train.err1 train.kap1 
##         38         39
round(crs$ada$model$errs[crs$ada$iter,], 2)
## train.err train.kap 
##      0.10      0.21
cat('Variables actually used in tree construction:\n')
## Variables actually used in tree construction:
print(sort(names(listAdaVarsUsed(crs$ada))))
## [1] "RMD_R10_Denominator" "RMD_Year"            "Source"             
## [4] "State_Region"
cat('\nFrequency of variables actually used:\n')
## 
## Frequency of variables actually used:
print(listAdaVarsUsed(crs$ada))
## 
## RMD_R10_Denominator            RMD_Year        State_Region              Source 
##                  50                  50                  49                  43
# Time taken: 1.14 secs

# Plot the error rate as we increase the number of trees.

plot(crs$ada)

# Plot the relative importance of the variables.

ada::varplot(crs$ada)

# Display tree number 1.

listTreesAda(crs$ada, 1)
## 
## Tree 1 of 50:
## n= 592 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##  1) root 592 0.2162162000 -1 (0.63271162 0.36728838)  
##    2) RMD_Year>=-0.252934 384 0.0692567600 -1 (0.82858636 0.17141364)  
##      4) RMD_Year>=0.4215567 230 0.0143581100 -1 (0.94267650 0.05732350) *
##      5) RMD_Year< 0.4215567 154 0.0548986500 -1 (0.64248883 0.35751117)  
##       10) State_Region=D1 New England,D2 Middle Atlantic,D3 East North Central,D5 South Atlantic 71 0.0109797300 -1 (0.85413745 0.14586255) *
##       11) State_Region=D4 West North Central,D6 East South Central,D7 West South Central,D8 Mountain,D9 Pacific 83 0.0261824300 1 (0.43897505 0.56102495)  
##         22) State_Region=D4 West North Central,D9 Pacific 38 0.0152027000 -1 (0.59322034 0.40677966)  
##           44) RMD_R10_Denominator>=-0.738634 24 0.0067567570 -1 (0.72413793 0.27586207) *
##           45) RMD_R10_Denominator< -0.738634 14 0.0033783780 1 (0.34426230 0.65573770) *
##         23) State_Region=D6 East South Central,D7 West South Central,D8 Mountain 45 0.0092905410 1 (0.29806452 0.70193548) *
##    3) RMD_Year< -0.252934 208 0.0287162200 1 (0.20411664 0.79588336)  
##      6) Source=addm,nsch 9 0.0008445946 -1 (0.91304348 0.08695652) *
##      7) Source=medi,sped 199 0.0219594600 1 (0.16475558 0.83524442) *

Xg Boost: Extreme Gradient Boost

if(!require(xgboost)){install.packages("xgboost")}
## Loading required package: xgboost
## 
## Attaching package: 'xgboost'
## The following object is masked from 'package:rattle':
## 
##     xgboost
library('xgboost')
#=======================================================================
# Rattle timestamp: 2019-12-24 11:21:50 x86_64-pc-linux-gnu 

# Extreme Boost 

# The `xgboost' package implements the extreme gradient boost algorithm.

# Build the Extreme Boost model.

set.seed(crv$seed)

crs$xgb <- xgboost(Prevalence_Risk2 ~ .,
  data              = crs$dataset[crs$train,c(crs$input, crs$target)],
  max_depth         = 6,
  eta               = 0.3, 
  num_parallel_tree = 1, 
  nthread           = 2, 
  nround            = 50,
  metrics           = 'error',
  objective         = 'binary:logistic')

# Print the results of the modelling.

print(crs$xgb)

cat('\nFinal iteration error rate:\n')
print(round(crs$xgb$evaluation_log[crs$xgb$niter, ], 2))

cat('\nImportance/Frequency of variables actually used:\n')
print(crs$imp <- importance(crs$xgb, crs$dataset[crs$train,c(crs$input, crs$target)]))

# Time taken: 0.10 secs

Note: Above R code generated from Rattle log cannot be executed directly due to: “Error in xgb.get.DMatrix(data, label, missing, weight): xgboost doesn’t support data.frame as input. Convert it to matrix first.”

In the workshop submission section, you are required to build xgboost model by fixing/handling this issue. References:

https://github.com/dd-consulting/DDC-Data-Science-R/blob/master/HousePriceAnalysisPrediction/codeR/House%20prices_%20Lasso%2C%20XGBoost%2C%20and%20a%20detailed%20EDA.pdf

https://github.com/dd-consulting/DDC-Data-Science-R/blob/master/Google%20Analytics%20Customer%20Revenue%20Prediction/code/Google%20Analytics%20Customer%20Revenue%20Prediction%20EDA.pdf

<h3>
Binary-Class Model: Neural Net (NN)
</h3>

if(!require(nnet)){install.packages("nnet")}
library('nnet')
#=======================================================================
# Rattle timestamp: 2019-12-24 11:46:00 x86_64-pc-linux-gnu 

# Neural Network 

# Build a neural network model using the nnet package.

library(nnet, quietly=TRUE)

# Build the NNet model.

set.seed(199)
crs$nnet <- nnet(as.factor(Prevalence_Risk2) ~ .,
    data=crs$dataset[crs$train,c(crs$input, crs$target)],
    size=10, skip=TRUE, MaxNWts=10000, trace=FALSE, maxit=100)

# Print the results of the modelling.

cat(sprintf("A %s network with %d weights.\n",
    paste(crs$nnet$n, collapse="-"),
    length(crs$nnet$wts)))
## A 13-10-1 network with 164 weights.
cat(sprintf("Inputs: %s.\n",
    paste(crs$nnet$coefnames, collapse=", ")))
## Inputs: Sourcemedi, Sourcensch, Sourcesped, State_RegionD2 Middle Atlantic, State_RegionD3 East North Central, State_RegionD4 West North Central, State_RegionD5 South Atlantic, State_RegionD6 East South Central, State_RegionD7 West South Central, State_RegionD8 Mountain, State_RegionD9 Pacific, RMD_Year, RMD_R10_Denominator.
cat(sprintf("Output: %s.\n",
    names(attr(crs$nnet$terms, "dataClasses"))[1]))
## Output: as.factor(Prevalence_Risk2).
cat(sprintf("Sum of Squares Residuals: %.4f.\n",
    sum(residuals(crs$nnet) ^ 2)))
## Sum of Squares Residuals: 36.0932.
cat("\n")
print(summary(crs$nnet))
## a 13-10-1 network with 164 weights
## options were - skip-layer connections  entropy fitting 
##   b->h1  i1->h1  i2->h1  i3->h1  i4->h1  i5->h1  i6->h1  i7->h1  i8->h1  i9->h1 
##  -18.43   -3.16    0.79  -31.17   18.33   36.73  -10.83  -30.05   46.71   21.06 
## i10->h1 i11->h1 i12->h1 i13->h1 
##    4.86   -0.54    6.24  -18.48 
##   b->h2  i1->h2  i2->h2  i3->h2  i4->h2  i5->h2  i6->h2  i7->h2  i8->h2  i9->h2 
##   25.05   34.57    0.03  -18.40    5.34    6.32  -26.56  -29.34   -0.14    7.41 
## i10->h2 i11->h2 i12->h2 i13->h2 
##   11.55   21.15   -3.66   43.18 
##   b->h3  i1->h3  i2->h3  i3->h3  i4->h3  i5->h3  i6->h3  i7->h3  i8->h3  i9->h3 
##  -17.59  -16.17    0.39    2.84   -0.30   -1.13    8.97   33.41    3.07   -2.11 
## i10->h3 i11->h3 i12->h3 i13->h3 
##    6.06   11.59   15.49  -30.61 
##   b->h4  i1->h4  i2->h4  i3->h4  i4->h4  i5->h4  i6->h4  i7->h4  i8->h4  i9->h4 
##   -2.34    3.83    0.78   13.98   -0.49    1.61    0.68    9.42    1.66   -0.34 
## i10->h4 i11->h4 i12->h4 i13->h4 
##   -2.58   -0.91    3.93   -2.87 
##   b->h5  i1->h5  i2->h5  i3->h5  i4->h5  i5->h5  i6->h5  i7->h5  i8->h5  i9->h5 
##    0.79   -6.39   -0.38   12.26   -2.18    2.50    9.63  -22.01  -12.95  -21.37 
## i10->h5 i11->h5 i12->h5 i13->h5 
##  -23.23  -23.84   17.23  -12.34 
##   b->h6  i1->h6  i2->h6  i3->h6  i4->h6  i5->h6  i6->h6  i7->h6  i8->h6  i9->h6 
##  -16.27  -38.93   -0.67   13.25  -10.10   -5.53  -24.36  -30.73   -8.52  -22.40 
## i10->h6 i11->h6 i12->h6 i13->h6 
##  -16.30   13.53   11.79   13.99 
##   b->h7  i1->h7  i2->h7  i3->h7  i4->h7  i5->h7  i6->h7  i7->h7  i8->h7  i9->h7 
##   -2.42   -2.23    0.02    8.23   -9.92   -5.26   -4.29  -18.93  -11.25   -4.30 
## i10->h7 i11->h7 i12->h7 i13->h7 
##   -3.95  -12.33   19.96    4.99 
##   b->h8  i1->h8  i2->h8  i3->h8  i4->h8  i5->h8  i6->h8  i7->h8  i8->h8  i9->h8 
##    0.22  -14.60   -0.06   12.87   15.56   27.27   29.37   11.69   21.73  -13.64 
## i10->h8 i11->h8 i12->h8 i13->h8 
##   29.77   14.84   18.18  -32.23 
##   b->h9  i1->h9  i2->h9  i3->h9  i4->h9  i5->h9  i6->h9  i7->h9  i8->h9  i9->h9 
##   -8.97  -12.47    0.57   -4.11    2.95   -0.35  -16.44   32.70   -3.12  -14.14 
## i10->h9 i11->h9 i12->h9 i13->h9 
##   15.66    4.33  -29.52    0.07 
##   b->h10  i1->h10  i2->h10  i3->h10  i4->h10  i5->h10  i6->h10  i7->h10 
##     5.54    24.66    -0.48     2.09    -3.54     7.65    -6.29    14.44 
##  i8->h10  i9->h10 i10->h10 i11->h10 i12->h10 i13->h10 
##     5.82     1.17     2.27    11.51    -7.31    19.73 
##   b->o  h1->o  h2->o  h3->o  h4->o  h5->o  h6->o  h7->o  h8->o  h9->o h10->o 
##   1.78 -24.65 -19.25  11.31  16.11  -8.23 -23.14  -8.93 -20.07   5.14  15.96 
##  i1->o  i2->o  i3->o  i4->o  i5->o  i6->o  i7->o  i8->o  i9->o i10->o i11->o 
##   3.69   0.59   1.90  -7.87   7.97   8.05 -24.15  27.42   0.25  12.31   2.46 
## i12->o i13->o 
##  -3.50   3.30
cat('\n')
# Time taken: 0.29 secs
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Evaluate Model (Classification: Binary-Class)

Binary-Class Classification: Prevalence_Risk2

crs$ada
crs$nnet
<h3>
Rattle: Evaluate Model (Classification): Error/Confusion matrix
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-24 12:07:18 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# Generate an Error Matrix for the Extreme Boost model.

# Obtain the response from the Extreme Boost model.

crs$pr <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Generate the confusion matrix showing counts.

rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2, crs$pr, count=TRUE)
##       Predicted
## Actual High Low Error
##   High  119  21  15.0
##   Low    22  93  19.1
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2, crs$pr))
##       Predicted
## Actual High  Low Error
##   High 46.7  8.2  15.0
##   Low   8.6 36.5  19.1
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 16.8
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 17.05
# Generate an Error Matrix for the Neural Net model.

# Obtain the response from the Neural Net model.

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)], type="class")

# Generate the confusion matrix showing counts.

rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2, crs$pr, count=TRUE)
##       Predicted
## Actual High Low Error
##   High  122  18  12.9
##   Low    17  98  14.8
# Generate the confusion matrix showing proportions.

(per <- rattle::errorMatrix(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2, crs$pr))
##       Predicted
## Actual High  Low Error
##   High 47.8  7.1  12.9
##   Low   6.7 38.4  14.8
# Calculate the overall error percentage.

cat(100-sum(diag(per), na.rm=TRUE))
## 13.8
# Calculate the averaged class error percentage.

cat(mean(per[,"Error"], na.rm=TRUE))
## 13.85
<h3>
Rattle: Evaluate Model (Classification): ROC
</h3>

ROC Curve: TPR (True Positive Rate) / Hit Rate / Recall / Sensitivity vs. FPR / 1- Specificity

if(!require(ROCR)){install.packages("ROCR")}
## Loading required package: ROCR
library('ROCR')
#=======================================================================
# Rattle timestamp: 2019-12-24 12:09:03 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# ROC Curve: requires the ROCR package.

library(ROCR)

# ROC Curve: requires the ggplot2 package.

library(ggplot2, quietly=TRUE)

# Generate an ROC Curve for the ada model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input, crs$target)], type="prob")[,2]

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}

pe <- performance(pred, "tpr", "fpr")
au <- performance(pred, "auc")@y.values[[1]]
pd <- data.frame(fpr=unlist(pe@x.values), tpr=unlist(pe@y.values))
p <- ggplot(pd, aes(x=fpr, y=tpr))
p <- p + geom_line(colour="red")
p <- p + xlab("False Positive Rate") + ylab("True Positive Rate")
p <- p + ggtitle("ROC Curve Extreme Boost ADV_ASD_State_R.csv [test] Prevalence_Risk2")
p <- p + theme(plot.title=element_text(size=10))
p <- p + geom_line(data=data.frame(), aes(x=c(0,1), y=c(0,1)), colour="grey")
p <- p + annotate("text", x=0.50, y=0.00, hjust=0, vjust=0, size=5,
                   label=paste("AUC =", round(au, 2)))
print(p)

# Calculate the area under the curve for the plot.


# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
performance(pred, "auc")
## An object of class "performance"
## Slot "x.name":
## [1] "None"
## 
## Slot "y.name":
## [1] "Area under the ROC curve"
## 
## Slot "alpha.name":
## [1] "none"
## 
## Slot "x.values":
## list()
## 
## Slot "y.values":
## [[1]]
## [1] 0.9240062
## 
## 
## Slot "alpha.values":
## list()
# ROC Curve: requires the ROCR package.

library(ROCR)

# ROC Curve: requires the ggplot2 package.

library(ggplot2, quietly=TRUE)

# Generate an ROC Curve for the nnet model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}

pe <- performance(pred, "tpr", "fpr")
au <- performance(pred, "auc")@y.values[[1]]
pd <- data.frame(fpr=unlist(pe@x.values), tpr=unlist(pe@y.values))
p <- ggplot(pd, aes(x=fpr, y=tpr))
p <- p + geom_line(colour="red")
p <- p + xlab("False Positive Rate") + ylab("True Positive Rate")
p <- p + ggtitle("ROC Curve Neural Net ADV_ASD_State_R.csv [test] Prevalence_Risk2")
p <- p + theme(plot.title=element_text(size=10))
p <- p + geom_line(data=data.frame(), aes(x=c(0,1), y=c(0,1)), colour="grey")
p <- p + annotate("text", x=0.50, y=0.00, hjust=0, vjust=0, size=5,
                   label=paste("AUC =", round(au, 2)))
print(p)

# Calculate the area under the curve for the plot.


# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
performance(pred, "auc")
## An object of class "performance"
## Slot "x.name":
## [1] "None"
## 
## Slot "y.name":
## [1] "Area under the ROC curve"
## 
## Slot "alpha.name":
## [1] "none"
## 
## Slot "x.values":
## list()
## 
## Slot "y.values":
## [[1]]
## [1] 0.9427329
## 
## 
## Slot "alpha.values":
## list()
<h3>
Rattle: Evaluate Model (Classification): Sensitivity
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-24 12:17:21 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# Sensitivity/Specificity Plot: requires the ROCR package

library(ROCR)

# Generate Sensitivity/Specificity Plot for ada model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input, crs$target)], type="prob")[,2]

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
ROCR::plot(performance(pred, "sens", "spec"), col="#CC0000FF", lty=1, add=FALSE)


# Sensitivity/Specificity Plot: requires the ROCR package

library(ROCR)

# Generate Sensitivity/Specificity Plot for nnet model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
ROCR::plot(performance(pred, "sens", "spec"), col="#00CCCCFF", lty=2, add=TRUE)


# Add a legend to the plot.

legend("bottomleft", c("ada","nnet"), col=rainbow(2, 1, .8), lty=1:2, title="Models", inset=c(0.05, 0.05))

# Add decorations to the plot.

title(main="Sensitivity/Specificity (tpr/tnr)  ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

<h3>
Rattle: Evaluate Model (Classification): Precision
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-24 12:20:14 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# Precision/Recall Plot: requires the ROCR package

library(ROCR)

# Generate a Precision/Recall Plot for the ada model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input, crs$target)], type="prob")[,2]

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
ROCR::plot(performance(pred, "prec", "rec"), col="#CC0000FF", lty=1, add=FALSE)


# Precision/Recall Plot: requires the ROCR package

library(ROCR)

# Generate a Precision/Recall Plot for the nnet model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}
ROCR::plot(performance(pred, "prec", "rec"), col="#00CCCCFF", lty=2, add=TRUE)


# Add a legend to the plot.

legend("bottomleft", c("ada","nnet"), col=rainbow(2, 1, .8), lty=1:2, title="Models", inset=c(0.05, 0.05))

# Add decorations to the plot.

title(main="Precision/Recall Plot  ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

<h3>
Rattle: Evaluate Model (Classification): Lift
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-24 12:11:55 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# Lift Chart: requires the ROCR package.

library(ROCR)

# Obtain predictions for the ada model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input, crs$target)], type="prob")[,2]

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}

# Convert rate of positive predictions to percentage.

per <- performance(pred, "lift", "rpp")
per@x.values[[1]] <- per@x.values[[1]]*100

# Plot the lift chart.
ROCR::plot(per, col="#CC0000FF", lty=1, xlab="Caseload (%)", add=FALSE)

# Lift Chart: requires the ROCR package.

library(ROCR)

# Obtain predictions for the nnet model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Remove observations with missing target.

no.miss   <- na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]$Prevalence_Risk2)
miss.list <- attr(no.miss, "na.action")
attributes(no.miss) <- NULL

if (length(miss.list))
{
  pred <- prediction(crs$pr[-miss.list], no.miss)
} else
{
  pred <- prediction(crs$pr, no.miss)
}

# Convert rate of positive predictions to percentage.

per <- performance(pred, "lift", "rpp")
per@x.values[[1]] <- per@x.values[[1]]*100

# Plot the lift chart.
ROCR::plot(per, col="#00CCCCFF", lty=2, xlab="Caseload (%)", add=TRUE)

# Add a legend to the plot.

legend("topright", c("ada","nnet"), col=rainbow(2, 1, .8), lty=1:2, title="Models", inset=c(0.05, 0.05))

# Add decorations to the plot.

title(main="Lift Chart  ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

<h3>
Rattle: Evaluate Model (Classification): Score/Write predicted results to CSV file.
</h3>
#=======================================================================
# Rattle timestamp: 2019-12-24 12:22:22 x86_64-pc-linux-gnu 

# Score the testing dataset. 

# Obtain probability scores for the Extreme Boost model on ADV_ASD_State_R.csv [test].

crs$pr_ada <- predict(crs$ada, newdata=crs$dataset[crs$test, c(crs$input)])

# Obtain probability scores for the Neural Net model on ADV_ASD_State_R.csv [test].

crs$pr_nnet <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input)], type="class")

# Extract the relevant variables from the dataset.

sdata <- crs$dataset[crs$test,]

# Output the combined data.

write.csv(cbind(sdata, crs$pr_ada, crs$pr_nnet), file="../reference/R rattle/ADV_ASD_State_R_test_score_all_Prevalence_Risk2.csv", row.names=FALSE)
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Train Model (Regression)

#=======================================================================
# Rattle timestamp: 2019-12-30 11:36:06 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(crv$seed)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("Source", "State_Region", "RMD_Year",
                   "RMD_R10_Denominator")

crs$numeric   <- c("RMD_Year", "RMD_R10_Denominator")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Denominator", "Lower.CI", "Upper.CI", "Year", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk2", "Prevalence_Risk4", "Year_Factor", "R10_Denominator")
crs$weights   <- NULL
crs$target
## [1] "Prevalence"
crs$input
## [1] "Source"              "State_Region"        "RMD_Year"           
## [4] "RMD_R10_Denominator"
<h3>
Regression Model: Decision Tree (DT)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:36:06 x86_64-pc-linux-gnu 

# Action the user selections from the Data tab. 

# Build the train/validate/test datasets.

# nobs=1692 train=1184 validate=254 test=254

set.seed(crv$seed)

crs$nobs <- nrow(crs$dataset)

crs$train <- sample(crs$nobs, 0.7*crs$nobs)

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  sample(0.15*crs$nobs) ->
crs$validate

crs$nobs %>%
  seq_len() %>%
  setdiff(crs$train) %>%
  setdiff(crs$validate) ->
crs$test

# The following variable selections have been noted.

crs$input     <- c("Source", "State_Region", "RMD_Year",
                   "RMD_R10_Denominator")

crs$numeric   <- c("RMD_Year", "RMD_R10_Denominator")

crs$categoric <- c("Source", "State_Region")

crs$target    <- "Prevalence"
crs$risk      <- NULL
crs$ident     <- NULL
crs$ignore    <- c("State", "Denominator", "Lower.CI", "Upper.CI", "Year", "Source_Full1", "State_Full1", "State_Full2", "Numerator_ASD", "Numerator_NonASD", "Proportion", "Chi_Wilson_Corrected_Lower.CI", "Chi_Wilson_Corrected_Upper.CI", "Male.Prevalence", "Male.Lower.CI", "Male.Upper.CI", "Female.Prevalence", "Female.Lower.CI", "Female.Upper.CI", "Non.hispanic.white.Prevalence", "Non.hispanic.white.Lower.CI", "Non.hispanic.white.Upper.CI", "Non.hispanic.black.Prevalence", "Non.hispanic.black.Lower.CI", "Non.hispanic.black.Upper.CI", "Hispanic.Prevalence", "Hispanic.Lower.CI", "Hispanic.Upper.CI", "Asian.or.Pacific.Islander.Prevalence", "Asian.or.Pacific.Islander.Lower.CI", "Asian.or.Pacific.Islander.Upper.CI", "Source_UC", "Source_Full3", "Prevalence_Risk2", "Prevalence_Risk4", "Year_Factor", "R10_Denominator")
crs$weights   <- NULL

#=======================================================================
# Rattle timestamp: 2019-12-30 11:41:57 x86_64-pc-linux-gnu 

# Decision Tree 

# The 'rpart' package provides the 'rpart' function.

library(rpart, quietly=TRUE)

# Reset the random number seed to obtain the same results each time.

set.seed(crv$seed)

# Build the Decision Tree model.

crs$rpart <- rpart(Prevalence ~ .,
    data=crs$dataset[crs$train, c(crs$input, crs$target)],
    method="anova",
    parms=list(split="information"),
    control=rpart.control(usesurrogate=0, 
        maxsurrogate=0),
    model=TRUE)

# Generate a textual view of the Decision Tree model.

print(crs$rpart)
## n= 1184 
## 
## node), split, n, deviance, yval
##       * denotes terminal node
## 
##  1) root 1184 38576.9200  7.213260  
##    2) RMD_R10_Denominator>=-2.544461 1111 19512.2000  6.315842  
##      4) RMD_Year< 0.08431134 576  4656.6530  4.046528  
##        8) RMD_Year< -0.5901794 283  1149.2920  3.036042 *
##        9) RMD_Year>=-0.5901794 293  2939.2910  5.022526 *
##      5) RMD_Year>=0.08431134 535  8695.6740  8.759065  
##       10) RMD_R10_Denominator>=-1.349522 491  6783.0690  8.309165  
##         20) RMD_Year< 0.7588021 276  3202.2730  7.038406 *
##         21) RMD_Year>=0.7588021 215  2562.9580  9.940465  
##           42) State_Region=D3 East North Central,D4 West North Central,D5 South Atlantic,D6 East South Central,D7 West South Central,D8 Mountain,D9 Pacific 176  1666.7780  9.128409 *
##           43) State_Region=D1 New England,D2 Middle Atlantic 39   256.3590 13.605130 *
##       11) RMD_R10_Denominator< -1.349522 44   704.1916 13.779550 *
##    3) RMD_R10_Denominator< -2.544461 73  4552.5300 20.871230  
##      6) RMD_Year< 1.348982 47  1809.3540 17.172340  
##       12) RMD_Year< 0.5058681 16   303.6700 12.075000 *
##       13) RMD_Year>=0.5058681 31   875.3897 19.803230 *
##      7) RMD_Year>=1.348982 26   937.7035 27.557690 *
printcp(crs$rpart)
## 
## Regression tree:
## rpart(formula = Prevalence ~ ., data = crs$dataset[crs$train, 
##     c(crs$input, crs$target)], method = "anova", model = TRUE, 
##     parms = list(split = "information"), control = rpart.control(usesurrogate = 0, 
##         maxsurrogate = 0))
## 
## Variables actually used in tree construction:
## [1] RMD_R10_Denominator RMD_Year            State_Region       
## 
## Root node error: 38577/1184 = 32.582
## 
## n= 1184 
## 
##         CP nsplit rel error  xerror     xstd
## 1 0.376188      0   1.00000 1.00111 0.075332
## 2 0.159678      1   0.62381 0.65358 0.034535
## 3 0.046802      2   0.46413 0.48765 0.030468
## 4 0.031325      3   0.41733 0.44447 0.027224
## 5 0.026385      4   0.38601 0.43760 0.026735
## 6 0.016586      5   0.35962 0.40183 0.025204
## 7 0.016339      6   0.34304 0.39030 0.025675
## 8 0.014726      7   0.32670 0.38049 0.025752
## 9 0.010000      8   0.31197 0.35776 0.024423
cat("\n")
# Time taken: 0.01 secs

# List the rules from the tree using a Rattle support function.

asRules(crs$rpart)
## 
##  Rule number: 9 [Prevalence=5.02252559726962 cover=293 (25%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year< 0.08431
##    RMD_Year>=-0.5902
## 
##  Rule number: 8 [Prevalence=3.03604240282686 cover=283 (24%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year< 0.08431
##    RMD_Year< -0.5902
## 
##  Rule number: 20 [Prevalence=7.03840579710145 cover=276 (23%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year< 0.7588
## 
##  Rule number: 42 [Prevalence=9.12840909090909 cover=176 (15%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D3 East North Central,D4 West North Central,D5 South Atlantic,D6 East South Central,D7 West South Central,D8 Mountain,D9 Pacific
## 
##  Rule number: 11 [Prevalence=13.7795454545455 cover=44 (4%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year>=0.08431
##    RMD_R10_Denominator< -1.35
## 
##  Rule number: 43 [Prevalence=13.6051282051282 cover=39 (3%)]
##    RMD_R10_Denominator>=-2.544
##    RMD_Year>=0.08431
##    RMD_R10_Denominator>=-1.35
##    RMD_Year>=0.7588
##    State_Region=D1 New England,D2 Middle Atlantic
## 
##  Rule number: 13 [Prevalence=19.8032258064516 cover=31 (3%)]
##    RMD_R10_Denominator< -2.544
##    RMD_Year< 1.349
##    RMD_Year>=0.5059
## 
##  Rule number: 7 [Prevalence=27.5576923076923 cover=26 (2%)]
##    RMD_R10_Denominator< -2.544
##    RMD_Year>=1.349
## 
##  Rule number: 12 [Prevalence=12.075 cover=16 (1%)]
##    RMD_R10_Denominator< -2.544
##    RMD_Year< 1.349
##    RMD_Year< 0.5059
# Adjust in-line plot size to M x N
options(repr.plot.width=8, repr.plot.height=6)
rpart.plot::prp(crs$rpart,
    type = 2, extra = "auto", nn = TRUE,
    under = FALSE, fallen.leaves = TRUE,
    digits = 2, varlen = 0, faclen = 0, 
#    roundint = TRUE,
    cex = NULL, tweak = 1,
#    clip.facs = FALSE, 
    clip.right.labs = TRUE,
    snip = FALSE,
    box.palette = "auto", shadow.col = 0)

<h3>
Regression Model: Random Forest (RF)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:45:04 x86_64-pc-linux-gnu 

# Build a Random Forest model using the traditional approach.

set.seed(crv$seed)

crs$rf <- randomForest::randomForest(Prevalence ~ .,
  data=crs$dataset[crs$train, c(crs$input, crs$target)], 
  ntree=500,
  mtry=2,
  importance=TRUE,
  na.action=randomForest::na.roughfix,
  replace=FALSE)

# Generate textual output of the 'Random Forest' model.

crs$rf
## 
## Call:
##  randomForest(formula = Prevalence ~ ., data = crs$dataset[crs$train,      c(crs$input, crs$target)], ntree = 500, mtry = 2, importance = TRUE,      replace = FALSE, na.action = randomForest::na.roughfix) 
##                Type of random forest: regression
##                      Number of trees: 500
## No. of variables tried at each split: 2
## 
##           Mean of squared residuals: 7.770573
##                     % Var explained: 76.15
# List the importance of the variables.

rn <- crs$rf %>%
    randomForest::importance() %>%
    round(2)
    rn[order(rn[,1], decreasing=TRUE),]
##                     %IncMSE IncNodePurity
## RMD_Year             114.09       7137.03
## State_Region          58.32       2156.68
## RMD_R10_Denominator   43.02       8889.71
## Source                25.21       3722.86
# Time taken: 1.17 secs

#=======================================================================
# Rattle timestamp: 2019-12-30 11:45:10 x86_64-pc-linux-gnu 

# Plot the relative importance of the variables.

p <- ggVarImp(crs$rf,
              title="Variable Importance Random Forest ADV_ASD_State_R.csv")
p

# Plot the error rate against the number of trees.

plot(crs$rf, main="")
legend("topright", c(""), text.col=1:6, lty=1:3, col=1:3)
title(main="Error Rates Random Forest ADV_ASD_State_R.csv",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))

# Display tree number 1.

printRandomForests(crs$rf, 1)
## Random Forest Model 1 
## 
## -------------------------------------------------------------
## Tree 1 Rule 1 Node 8 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year <= 0.505868069607446
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 2 Node 9 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year <= 0.505868069607446
## 3: State_Region IN ("D3 East North Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 3 Node 16 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.94222248494914
## 4: RMD_Year <= 1.18035882908404
## -----------------------------------------------------------------
## Tree 1 Rule 4 Node 17 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator <= -3.94222248494914
## 4: RMD_Year > 1.18035882908404
## -----------------------------------------------------------------
## Tree 1 Rule 5 Node 18 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.94222248494914
## 4: State_Region IN ("D3 East North Central", "D4 West North Central", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 6 Node 44 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.94222248494914
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator <= -3.93731741271895
## -----------------------------------------------------------------
## Tree 1 Rule 7 Node 45 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.94222248494914
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 6: RMD_R10_Denominator > -3.93731741271895
## -----------------------------------------------------------------
## Tree 1 Rule 8 Node 46 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.94222248494914
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 5: State_Region IN ("D5 South Atlantic", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 9 Node 47 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator <= -3.89236192492941
## 2: RMD_Year > 0.505868069607446
## 3: RMD_R10_Denominator > -3.94222248494914
## 4: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 5: State_Region IN ("D5 South Atlantic", "D9 Pacific")
## 6: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 1 Rule 10 Node 48 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("sped")
## 5: RMD_Year <= -0.168622689869149
## 6: RMD_Year <= -0.843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 11 Node 49 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("sped")
## 5: RMD_Year <= -0.168622689869149
## 6: RMD_Year > -0.843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 12 Node 31 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("sped")
## 5: RMD_Year > -0.168622689869149
## -----------------------------------------------------------------
## Tree 1 Rule 13 Node 210 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D5 South Atlantic")
## 10: RMD_R10_Denominator <= -1.29601059896875
## -----------------------------------------------------------------
## Tree 1 Rule 14 Node 211 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D5 South Atlantic")
## 10: RMD_R10_Denominator > -1.29601059896875
## -----------------------------------------------------------------
## Tree 1 Rule 15 Node 276 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= -0.590179414542021
## 11: RMD_R10_Denominator <= -1.26142623539691
## -----------------------------------------------------------------
## Tree 1 Rule 16 Node 277 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= -0.590179414542021
## 11: RMD_R10_Denominator > -1.26142623539691
## -----------------------------------------------------------------
## Tree 1 Rule 17 Node 278 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > -0.590179414542021
## 11: RMD_R10_Denominator <= -1.33726802449106
## -----------------------------------------------------------------
## Tree 1 Rule 18 Node 372 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > -0.590179414542021
## 11: RMD_R10_Denominator > -1.33726802449106
## 12: RMD_R10_Denominator <= -1.17416513582869
## 13: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 19 Node 373 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > -0.590179414542021
## 11: RMD_R10_Denominator > -1.33726802449106
## 12: RMD_R10_Denominator <= -1.17416513582869
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 20 Node 333 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > -0.590179414542021
## 11: RMD_R10_Denominator > -1.33726802449106
## 12: RMD_R10_Denominator > -1.17416513582869
## -----------------------------------------------------------------
## Tree 1 Rule 21 Node 156 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 9: RMD_R10_Denominator <= -0.909215426442246
## -----------------------------------------------------------------
## Tree 1 Rule 22 Node 157 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("medi")
## 8: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 9: RMD_R10_Denominator > -0.909215426442246
## -----------------------------------------------------------------
## Tree 1 Rule 23 Node 158 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 24 Node 334 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -1.49998104972455
## 11: RMD_Year <= -0.674490759476595
## 12: State_Region IN ("D3 East North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 25 Node 374 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -1.49998104972455
## 11: RMD_Year <= -0.674490759476595
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator <= -1.93398617830854
## -----------------------------------------------------------------
## Tree 1 Rule 26 Node 375 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -1.49998104972455
## 11: RMD_Year <= -0.674490759476595
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: RMD_R10_Denominator > -1.93398617830854
## -----------------------------------------------------------------
## Tree 1 Rule 27 Node 281 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= -1.49998104972455
## 11: RMD_Year > -0.674490759476595
## -----------------------------------------------------------------
## Tree 1 Rule 28 Node 215 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year <= -0.337245379738298
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > -1.49998104972455
## -----------------------------------------------------------------
## Tree 1 Rule 29 Node 216 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year > -0.337245379738298
## 9: RMD_Year <= 0
## 10: RMD_R10_Denominator <= -1.93619615650655
## -----------------------------------------------------------------
## Tree 1 Rule 30 Node 217 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year > -0.337245379738298
## 9: RMD_Year <= 0
## 10: RMD_R10_Denominator > -1.93619615650655
## -----------------------------------------------------------------
## Tree 1 Rule 31 Node 161 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: Source IN ("addm", "nsch", "sped")
## 8: RMD_Year > -0.337245379738298
## 9: RMD_Year > 0
## -----------------------------------------------------------------
## Tree 1 Rule 32 Node 162 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D1 New England")
## 7: RMD_R10_Denominator <= -1.26958413887206
## 8: Source IN ("addm", "medi", "sped")
## 9: RMD_R10_Denominator <= -1.4071919336361
## -----------------------------------------------------------------
## Tree 1 Rule 33 Node 163 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D1 New England")
## 7: RMD_R10_Denominator <= -1.26958413887206
## 8: Source IN ("addm", "medi", "sped")
## 9: RMD_R10_Denominator > -1.4071919336361
## -----------------------------------------------------------------
## Tree 1 Rule 34 Node 109 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D1 New England")
## 7: RMD_R10_Denominator <= -1.26958413887206
## 8: Source IN ("nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 35 Node 75 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator <= -0.888889677818923
## 6: State_Region IN ("D1 New England")
## 7: RMD_R10_Denominator > -1.26958413887206
## -----------------------------------------------------------------
## Tree 1 Rule 36 Node 33 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator <= -0.855764289999938
## 4: Source IN ("addm", "medi", "nsch")
## 5: RMD_R10_Denominator > -0.888889677818923
## -----------------------------------------------------------------
## Tree 1 Rule 37 Node 164 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator <= 0.209776307847675
## 8: RMD_Year <= -0.927424794280318
## 9: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 38 Node 218 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator <= 0.209776307847675
## 8: RMD_Year <= -0.927424794280318
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 39 Node 219 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator <= 0.209776307847675
## 8: RMD_Year <= -0.927424794280318
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 40 Node 111 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator <= 0.209776307847675
## 8: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 41 Node 112 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator <= 0.273648134902801
## -----------------------------------------------------------------
## Tree 1 Rule 42 Node 282 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator <= 0.522921570926857
## 10: RMD_Year <= -0.927424794280318
## 11: State_Region IN ("D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 43 Node 283 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator <= 0.522921570926857
## 10: RMD_Year <= -0.927424794280318
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 44 Node 221 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator <= 0.522921570926857
## 10: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 45 Node 222 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 46 Node 284 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 47 Node 336 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator <= 0.701287967023711
## -----------------------------------------------------------------
## Tree 1 Rule 48 Node 412 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.701287967023711
## 13: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.705729824934705
## -----------------------------------------------------------------
## Tree 1 Rule 49 Node 434 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.701287967023711
## 13: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.705729824934705
## 15: RMD_Year <= -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 50 Node 446 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.701287967023711
## 13: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.705729824934705
## 15: RMD_Year > -0.927424794280318
## 16: RMD_R10_Denominator <= 0.935538242399887
## -----------------------------------------------------------------
## Tree 1 Rule 51 Node 447 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.701287967023711
## 13: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.705729824934705
## 15: RMD_Year > -0.927424794280318
## 16: RMD_R10_Denominator > 0.935538242399887
## -----------------------------------------------------------------
## Tree 1 Rule 52 Node 377 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("sped")
## 7: RMD_R10_Denominator > 0.209776307847675
## 8: RMD_R10_Denominator > 0.273648134902801
## 9: RMD_R10_Denominator > 0.522921570926857
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: RMD_R10_Denominator > 0.701287967023711
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 53 Node 168 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.243286152344291
## 9: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 1 Rule 54 Node 286 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.243286152344291
## 9: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.0476578896357959
## 11: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 55 Node 287 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.243286152344291
## 9: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.0476578896357959
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 56 Node 225 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator <= 0.243286152344291
## 9: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.0476578896357959
## -----------------------------------------------------------------
## Tree 1 Rule 57 Node 115 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D1 New England", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_R10_Denominator > 0.243286152344291
## -----------------------------------------------------------------
## Tree 1 Rule 58 Node 170 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator <= -0.192303976449642
## 9: RMD_R10_Denominator <= -0.783005101833257
## -----------------------------------------------------------------
## Tree 1 Rule 59 Node 226 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator <= -0.192303976449642
## 9: RMD_R10_Denominator > -0.783005101833257
## 10: RMD_R10_Denominator <= -0.596462473246108
## -----------------------------------------------------------------
## Tree 1 Rule 60 Node 288 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator <= -0.192303976449642
## 9: RMD_R10_Denominator > -0.783005101833257
## 10: RMD_R10_Denominator > -0.596462473246108
## 11: RMD_R10_Denominator <= -0.268671357080555
## -----------------------------------------------------------------
## Tree 1 Rule 61 Node 289 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator <= -0.192303976449642
## 9: RMD_R10_Denominator > -0.783005101833257
## 10: RMD_R10_Denominator > -0.596462473246108
## 11: RMD_R10_Denominator > -0.268671357080555
## -----------------------------------------------------------------
## Tree 1 Rule 62 Node 228 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator <= 0.51654730014004
## 10: State_Region IN ("D7 West South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 63 Node 290 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator <= 0.51654730014004
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= -1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 64 Node 378 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator <= 0.51654730014004
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 13: RMD_Year <= -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 65 Node 379 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator <= 0.51654730014004
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 13: RMD_Year > -0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 66 Node 339 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator <= 0.51654730014004
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > -1.09604748414947
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 67 Node 292 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator > 0.51654730014004
## 10: RMD_R10_Denominator <= 0.920343074863425
## 11: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 68 Node 293 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator > 0.51654730014004
## 10: RMD_R10_Denominator <= 0.920343074863425
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 69 Node 231 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year <= -0.75880210441117
## 6: Source IN ("addm", "medi", "nsch")
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central")
## 8: RMD_R10_Denominator > -0.192303976449642
## 9: RMD_R10_Denominator > 0.51654730014004
## 10: RMD_R10_Denominator > 0.920343074863425
## -----------------------------------------------------------------
## Tree 1 Rule 70 Node 80 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D6 East South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 71 Node 174 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("sped")
## 9: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 72 Node 232 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("sped")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.21805016946628
## -----------------------------------------------------------------
## Tree 1 Rule 73 Node 233 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("sped")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.21805016946628
## -----------------------------------------------------------------
## Tree 1 Rule 74 Node 234 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("addm", "medi", "nsch")
## 9: State_Region IN ("D7 West South Central")
## 10: RMD_Year <= -0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 75 Node 235 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("addm", "medi", "nsch")
## 9: State_Region IN ("D7 West South Central")
## 10: RMD_Year > -0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 76 Node 177 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D6 East South Central", "D7 West South Central", "D8 Mountain")
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: Source IN ("addm", "medi", "nsch")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 77 Node 120 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -0.0851994441619026
## 8: Source IN ("sped")
## -----------------------------------------------------------------
## Tree 1 Rule 78 Node 121 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator <= -0.0851994441619026
## 8: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 79 Node 178 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## 9: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 80 Node 236 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.00314246228434489
## -----------------------------------------------------------------
## Tree 1 Rule 81 Node 340 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.00314246228434489
## 11: State_Region IN ("D5 South Atlantic")
## 12: Source IN ("sped")
## -----------------------------------------------------------------
## Tree 1 Rule 82 Node 341 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.00314246228434489
## 11: State_Region IN ("D5 South Atlantic")
## 12: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 83 Node 295 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D1 New England", "D4 West North Central", "D5 South Atlantic")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.00314246228434489
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 84 Node 180 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator <= 0.530024869530886
## -----------------------------------------------------------------
## Tree 1 Rule 85 Node 238 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.530024869530886
## 10: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 86 Node 342 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.530024869530886
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 1.42113303893631
## 12: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 87 Node 380 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.530024869530886
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 1.42113303893631
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_Year <= -0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 88 Node 381 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.530024869530886
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator <= 1.42113303893631
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_Year > -0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 89 Node 297 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year <= -0.421556724672872
## 5: RMD_Year > -0.75880210441117
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.0851994441619026
## 8: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 9: RMD_R10_Denominator > 0.530024869530886
## 10: Source IN ("addm", "nsch", "sped")
## 11: RMD_R10_Denominator > 1.42113303893631
## -----------------------------------------------------------------
## Tree 1 Rule 90 Node 124 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_R10_Denominator <= -0.103542616970137
## -----------------------------------------------------------------
## Tree 1 Rule 91 Node 182 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_R10_Denominator > -0.103542616970137
## 9: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 92 Node 240 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_R10_Denominator > -0.103542616970137
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= 0.344159439399148
## -----------------------------------------------------------------
## Tree 1 Rule 93 Node 241 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year <= -0.252934034803723
## 8: RMD_R10_Denominator > -0.103542616970137
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > 0.344159439399148
## -----------------------------------------------------------------
## Tree 1 Rule 94 Node 126 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year > -0.252934034803723
## 8: Source IN ("sped")
## -----------------------------------------------------------------
## Tree 1 Rule 95 Node 127 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year <= -0.0843113449345744
## 7: RMD_Year > -0.252934034803723
## 8: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 96 Node 128 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= -0.088400441707716
## 8: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 97 Node 129 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator <= -0.088400441707716
## 8: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 98 Node 184 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > -0.088400441707716
## 8: Source IN ("sped")
## 9: RMD_Year <= 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 99 Node 242 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > -0.088400441707716
## 8: Source IN ("sped")
## 9: RMD_Year > 0.0843113449345744
## 10: RMD_R10_Denominator <= 0.108118230529643
## -----------------------------------------------------------------
## Tree 1 Rule 100 Node 298 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > -0.088400441707716
## 8: Source IN ("sped")
## 9: RMD_Year > 0.0843113449345744
## 10: RMD_R10_Denominator > 0.108118230529643
## 11: State_Region IN ("D7 West South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 101 Node 299 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > -0.088400441707716
## 8: Source IN ("sped")
## 9: RMD_Year > 0.0843113449345744
## 10: RMD_R10_Denominator > 0.108118230529643
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 102 Node 131 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D7 West South Central", "D8 Mountain")
## 6: RMD_Year > -0.0843113449345744
## 7: RMD_R10_Denominator > -0.088400441707716
## 8: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 103 Node 132 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator <= -0.551103724395262
## -----------------------------------------------------------------
## Tree 1 Rule 104 Node 300 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator > -0.551103724395262
## 9: RMD_Year <= -0.0843113449345744
## 10: RMD_R10_Denominator <= 0.534419753822836
## 11: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 105 Node 301 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator > -0.551103724395262
## 9: RMD_Year <= -0.0843113449345744
## 10: RMD_R10_Denominator <= 0.534419753822836
## 11: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 106 Node 302 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator > -0.551103724395262
## 9: RMD_Year <= -0.0843113449345744
## 10: RMD_R10_Denominator > 0.534419753822836
## 11: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 107 Node 303 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator > -0.551103724395262
## 9: RMD_Year <= -0.0843113449345744
## 10: RMD_R10_Denominator > 0.534419753822836
## 11: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 108 Node 187 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year <= 0.0843113449345744
## 8: RMD_R10_Denominator > -0.551103724395262
## 9: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 109 Node 246 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year > 0.0843113449345744
## 8: Source IN ("sped")
## 9: State_Region IN ("D5 South Atlantic")
## 10: RMD_Year <= 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 110 Node 247 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year > 0.0843113449345744
## 8: Source IN ("sped")
## 9: State_Region IN ("D5 South Atlantic")
## 10: RMD_Year > 0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 111 Node 189 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year > 0.0843113449345744
## 8: Source IN ("sped")
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 112 Node 135 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D1 New England", "D5 South Atlantic")
## 7: RMD_Year > 0.0843113449345744
## 8: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 113 Node 190 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator <= -0.583026647171076
## 8: Source IN ("medi")
## 9: RMD_Year <= -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 114 Node 191 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator <= -0.583026647171076
## 8: Source IN ("medi")
## 9: RMD_Year > -0.252934034803723
## -----------------------------------------------------------------
## Tree 1 Rule 115 Node 137 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator <= -0.583026647171076
## 8: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 116 Node 248 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator <= 0.0240371119577379
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator <= -0.562412741364026
## -----------------------------------------------------------------
## Tree 1 Rule 117 Node 249 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator <= 0.0240371119577379
## 9: Source IN ("addm", "nsch", "sped")
## 10: RMD_R10_Denominator > -0.562412741364026
## -----------------------------------------------------------------
## Tree 1 Rule 118 Node 304 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator <= 0.0240371119577379
## 9: Source IN ("medi")
## 10: RMD_R10_Denominator <= -0.0695414286225614
## 11: RMD_Year <= 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 119 Node 305 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator <= 0.0240371119577379
## 9: Source IN ("medi")
## 10: RMD_R10_Denominator <= -0.0695414286225614
## 11: RMD_Year > 0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 120 Node 251 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator <= 0.0240371119577379
## 9: Source IN ("medi")
## 10: RMD_R10_Denominator > -0.0695414286225614
## -----------------------------------------------------------------
## Tree 1 Rule 121 Node 344 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator <= 0.477639474216598
## 11: RMD_Year <= 0.168622689869149
## 12: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 122 Node 345 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator <= 0.477639474216598
## 11: RMD_Year <= 0.168622689869149
## 12: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 123 Node 307 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator <= 0.477639474216598
## 11: RMD_Year > 0.168622689869149
## -----------------------------------------------------------------
## Tree 1 Rule 124 Node 308 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator > 0.477639474216598
## 11: RMD_R10_Denominator <= 0.563282487895023
## -----------------------------------------------------------------
## Tree 1 Rule 125 Node 309 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D6 East South Central")
## 10: RMD_R10_Denominator > 0.477639474216598
## 11: RMD_R10_Denominator > 0.563282487895023
## -----------------------------------------------------------------
## Tree 1 Rule 126 Node 310 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 127 Node 414 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("medi")
## 13: RMD_Year <= -0.0843113449345744
## 14: RMD_R10_Denominator <= 0.583796425003578
## -----------------------------------------------------------------
## Tree 1 Rule 128 Node 415 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("medi")
## 13: RMD_Year <= -0.0843113449345744
## 14: RMD_R10_Denominator > 0.583796425003578
## -----------------------------------------------------------------
## Tree 1 Rule 129 Node 383 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("medi")
## 13: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 130 Node 384 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator <= 0.431284303288301
## -----------------------------------------------------------------
## Tree 1 Rule 131 Node 436 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator > 0.431284303288301
## 14: RMD_R10_Denominator <= 1.13069382531735
## 15: RMD_Year <= -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 132 Node 437 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator > 0.431284303288301
## 14: RMD_R10_Denominator <= 1.13069382531735
## 15: RMD_Year > -0.0843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 133 Node 417 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year <= 0.0843113449345744
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 12: Source IN ("addm", "nsch", "sped")
## 13: RMD_R10_Denominator > 0.431284303288301
## 14: RMD_R10_Denominator > 1.13069382531735
## -----------------------------------------------------------------
## Tree 1 Rule 134 Node 348 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("medi")
## 12: RMD_R10_Denominator <= 0.261938478142028
## -----------------------------------------------------------------
## Tree 1 Rule 135 Node 386 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("medi")
## 12: RMD_R10_Denominator > 0.261938478142028
## 13: State_Region IN ("D2 Middle Atlantic", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 136 Node 387 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("medi")
## 12: RMD_R10_Denominator > 0.261938478142028
## 13: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 137 Node 388 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: State_Region IN ("D1 New England", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 138 Node 418 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: State_Region IN ("D2 Middle Atlantic", "D9 Pacific")
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 139 Node 419 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 13: State_Region IN ("D2 Middle Atlantic", "D9 Pacific")
## 14: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 140 Node 351 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year <= 0.421556724672872
## 3: RMD_R10_Denominator > -0.855764289999938
## 4: RMD_Year > -0.421556724672872
## 5: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## 6: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 7: RMD_R10_Denominator > -0.583026647171076
## 8: RMD_R10_Denominator > 0.0240371119577379
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 10: RMD_Year > 0.0843113449345744
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 141 Node 60 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator <= -1.26406193095431
## 6: RMD_Year <= 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 142 Node 61 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator <= -1.26406193095431
## 6: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 143 Node 352 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D4 West North Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: RMD_R10_Denominator <= -1.24495343406708
## -----------------------------------------------------------------
## Tree 1 Rule 144 Node 390 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D4 West North Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: RMD_R10_Denominator > -1.24495343406708
## 13: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 145 Node 391 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D4 West North Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: RMD_R10_Denominator > -1.24495343406708
## 13: Source IN ("addm", "nsch", "sped")
## -----------------------------------------------------------------
## Tree 1 Rule 146 Node 315 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D4 West North Central", "D8 Mountain", "D9 Pacific")
## 11: RMD_Year > 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 147 Node 316 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central")
## 11: RMD_R10_Denominator <= -1.16220435659487
## -----------------------------------------------------------------
## Tree 1 Rule 148 Node 317 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year <= 1.26467017401862
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central")
## 11: RMD_R10_Denominator > -1.16220435659487
## -----------------------------------------------------------------
## Tree 1 Rule 149 Node 258 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year > 1.26467017401862
## 10: RMD_R10_Denominator <= -1.12355284415185
## -----------------------------------------------------------------
## Tree 1 Rule 150 Node 259 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator <= -0.745648609207454
## 9: RMD_Year > 1.26467017401862
## 10: RMD_R10_Denominator > -1.12355284415185
## -----------------------------------------------------------------
## Tree 1 Rule 151 Node 141 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator <= -0.69136996283611
## 8: RMD_R10_Denominator > -0.745648609207454
## -----------------------------------------------------------------
## Tree 1 Rule 152 Node 142 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator <= -0.651363208640878
## -----------------------------------------------------------------
## Tree 1 Rule 153 Node 438 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator <= 0.116747086143725
## 14: RMD_R10_Denominator <= -0.197997481260125
## 15: RMD_R10_Denominator <= -0.251361821640133
## -----------------------------------------------------------------
## Tree 1 Rule 154 Node 439 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator <= 0.116747086143725
## 14: RMD_R10_Denominator <= -0.197997481260125
## 15: RMD_R10_Denominator > -0.251361821640133
## -----------------------------------------------------------------
## Tree 1 Rule 155 Node 421 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator <= 0.116747086143725
## 14: RMD_R10_Denominator > -0.197997481260125
## -----------------------------------------------------------------
## Tree 1 Rule 156 Node 422 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator > 0.116747086143725
## 14: RMD_R10_Denominator <= 0.149440454561379
## -----------------------------------------------------------------
## Tree 1 Rule 157 Node 440 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator > 0.116747086143725
## 14: RMD_R10_Denominator > 0.149440454561379
## 15: RMD_Year <= 0.843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 158 Node 441 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_R10_Denominator > 0.116747086143725
## 14: RMD_R10_Denominator > 0.149440454561379
## 15: RMD_Year > 0.843113449345744
## -----------------------------------------------------------------
## Tree 1 Rule 159 Node 355 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("addm", "nsch", "sped")
## 12: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 160 Node 442 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.192271829284555
## 15: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 161 Node 448 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.192271829284555
## 15: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 16: RMD_R10_Denominator <= -0.46665082390965
## -----------------------------------------------------------------
## Tree 1 Rule 162 Node 452 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.192271829284555
## 15: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 16: RMD_R10_Denominator > -0.46665082390965
## 17: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 18: RMD_R10_Denominator <= 0.160781227695729
## -----------------------------------------------------------------
## Tree 1 Rule 163 Node 453 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.192271829284555
## 15: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 16: RMD_R10_Denominator > -0.46665082390965
## 17: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D7 West South Central", "D8 Mountain")
## 18: RMD_R10_Denominator > 0.160781227695729
## -----------------------------------------------------------------
## Tree 1 Rule 164 Node 451 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator <= 0.192271829284555
## 15: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 16: RMD_R10_Denominator > -0.46665082390965
## 17: State_Region IN ("D6 East South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 165 Node 425 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 14: RMD_R10_Denominator > 0.192271829284555
## -----------------------------------------------------------------
## Tree 1 Rule 166 Node 395 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year <= 0.75880210441117
## 13: State_Region IN ("D4 West North Central")
## -----------------------------------------------------------------
## Tree 1 Rule 167 Node 396 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year > 0.75880210441117
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 168 Node 397 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year <= 1.26467017401862
## 11: Source IN ("medi")
## 12: RMD_Year > 0.75880210441117
## 13: State_Region IN ("D4 West North Central", "D5 South Atlantic", "D6 East South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 169 Node 358 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year > 1.26467017401862
## 11: RMD_R10_Denominator <= 0.230146872707584
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 170 Node 398 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year > 1.26467017401862
## 11: RMD_R10_Denominator <= 0.230146872707584
## 12: State_Region IN ("D4 West North Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_Year <= 1.43329286388776
## -----------------------------------------------------------------
## Tree 1 Rule 171 Node 399 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year > 1.26467017401862
## 11: RMD_R10_Denominator <= 0.230146872707584
## 12: State_Region IN ("D4 West North Central", "D7 West South Central", "D8 Mountain")
## 13: RMD_Year > 1.43329286388776
## -----------------------------------------------------------------
## Tree 1 Rule 172 Node 321 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator <= 0.318067677577872
## 10: RMD_Year > 1.26467017401862
## 11: RMD_R10_Denominator > 0.230146872707584
## -----------------------------------------------------------------
## Tree 1 Rule 173 Node 360 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 174 Node 400 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 175 Node 426 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: Source IN ("addm", "nsch", "sped")
## 14: State_Region IN ("D5 South Atlantic", "D7 West South Central")
## -----------------------------------------------------------------
## Tree 1 Rule 176 Node 427 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year <= 0.75880210441117
## 12: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 13: Source IN ("addm", "nsch", "sped")
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 177 Node 402 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year > 0.75880210441117
## 12: RMD_Year <= 1.34898151895319
## 13: RMD_R10_Denominator <= 0.408862550879613
## -----------------------------------------------------------------
## Tree 1 Rule 178 Node 403 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year > 0.75880210441117
## 12: RMD_Year <= 1.34898151895319
## 13: RMD_R10_Denominator > 0.408862550879613
## -----------------------------------------------------------------
## Tree 1 Rule 179 Node 363 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D9 Pacific")
## 11: RMD_Year > 0.75880210441117
## 12: RMD_Year > 1.34898151895319
## -----------------------------------------------------------------
## Tree 1 Rule 180 Node 263 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator <= 0.517765044440116
## 7: RMD_R10_Denominator > -0.69136996283611
## 8: RMD_R10_Denominator > -0.651363208640878
## 9: RMD_R10_Denominator > 0.318067677577872
## 10: State_Region IN ("D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 181 Node 264 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("addm", "medi", "nsch")
## 10: State_Region IN ("D7 West South Central", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 182 Node 364 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("addm", "medi", "nsch")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain")
## 11: RMD_R10_Denominator <= 0.683831929863374
## 12: RMD_R10_Denominator <= 0.631194192500048
## -----------------------------------------------------------------
## Tree 1 Rule 183 Node 365 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("addm", "medi", "nsch")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain")
## 11: RMD_R10_Denominator <= 0.683831929863374
## 12: RMD_R10_Denominator > 0.631194192500048
## -----------------------------------------------------------------
## Tree 1 Rule 184 Node 366 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("addm", "medi", "nsch")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain")
## 11: RMD_R10_Denominator > 0.683831929863374
## 12: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 185 Node 367 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("addm", "medi", "nsch")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D8 Mountain")
## 11: RMD_R10_Denominator > 0.683831929863374
## 12: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 186 Node 266 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 187 Node 326 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator <= 0.721061845750619
## -----------------------------------------------------------------
## Tree 1 Rule 188 Node 404 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator <= 1.01444283351515
## 13: RMD_R10_Denominator <= 0.723343366272093
## -----------------------------------------------------------------
## Tree 1 Rule 189 Node 428 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator <= 1.01444283351515
## 13: RMD_R10_Denominator > 0.723343366272093
## 14: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 190 Node 444 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator <= 1.01444283351515
## 13: RMD_R10_Denominator > 0.723343366272093
## 14: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 15: RMD_R10_Denominator <= 0.914709842315939
## -----------------------------------------------------------------
## Tree 1 Rule 191 Node 445 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator <= 1.01444283351515
## 13: RMD_R10_Denominator > 0.723343366272093
## 14: State_Region IN ("D3 East North Central", "D5 South Atlantic")
## 15: RMD_R10_Denominator > 0.914709842315939
## -----------------------------------------------------------------
## Tree 1 Rule 192 Node 406 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator > 1.01444283351515
## 13: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## -----------------------------------------------------------------
## Tree 1 Rule 193 Node 407 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 0.927424794280318
## 9: Source IN ("sped")
## 10: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 11: RMD_R10_Denominator > 0.721061845750619
## 12: RMD_R10_Denominator > 1.01444283351515
## 13: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 194 Node 268 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 10: RMD_Year <= 1.26467017401862
## -----------------------------------------------------------------
## Tree 1 Rule 195 Node 269 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 10: RMD_Year > 1.26467017401862
## -----------------------------------------------------------------
## Tree 1 Rule 196 Node 328 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.724726620413951
## 11: RMD_R10_Denominator <= 0.645391206856512
## -----------------------------------------------------------------
## Tree 1 Rule 197 Node 329 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator <= 0.724726620413951
## 11: RMD_R10_Denominator > 0.645391206856512
## -----------------------------------------------------------------
## Tree 1 Rule 198 Node 408 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year <= 1.26467017401862
## 13: RMD_Year <= 1.09604748414947
## -----------------------------------------------------------------
## Tree 1 Rule 199 Node 430 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year <= 1.26467017401862
## 13: RMD_Year > 1.09604748414947
## 14: RMD_R10_Denominator <= 1.08010596289803
## -----------------------------------------------------------------
## Tree 1 Rule 200 Node 431 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year <= 1.26467017401862
## 13: RMD_Year > 1.09604748414947
## 14: RMD_R10_Denominator > 1.08010596289803
## -----------------------------------------------------------------
## Tree 1 Rule 201 Node 432 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year > 1.26467017401862
## 13: RMD_R10_Denominator <= 1.43291486349462
## 14: RMD_Year <= 1.43329286388776
## -----------------------------------------------------------------
## Tree 1 Rule 202 Node 433 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year > 1.26467017401862
## 13: RMD_R10_Denominator <= 1.43291486349462
## 14: RMD_Year > 1.43329286388776
## -----------------------------------------------------------------
## Tree 1 Rule 203 Node 411 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain")
## 12: RMD_Year > 1.26467017401862
## 13: RMD_R10_Denominator > 1.43291486349462
## -----------------------------------------------------------------
## Tree 1 Rule 204 Node 331 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 0.927424794280318
## 9: State_Region IN ("D3 East North Central", "D5 South Atlantic", "D9 Pacific")
## 10: RMD_R10_Denominator > 0.724726620413951
## 11: State_Region IN ("D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 205 Node 146 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D4 West North Central")
## 8: RMD_R10_Denominator <= 0.597270201293811
## -----------------------------------------------------------------
## Tree 1 Rule 206 Node 147 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("medi", "sped")
## 5: RMD_R10_Denominator > -1.26406193095431
## 6: RMD_R10_Denominator > 0.517765044440116
## 7: State_Region IN ("D4 West North Central")
## 8: RMD_R10_Denominator > 0.597270201293811
## -----------------------------------------------------------------
## Tree 1 Rule 207 Node 64 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("addm", "nsch")
## 5: RMD_Year <= 1.01173613921489
## 6: RMD_Year <= 0.674490759476595
## -----------------------------------------------------------------
## Tree 1 Rule 208 Node 96 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("addm", "nsch")
## 5: RMD_Year <= 1.01173613921489
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator <= -1.93273567078976
## -----------------------------------------------------------------
## Tree 1 Rule 209 Node 97 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("addm", "nsch")
## 5: RMD_Year <= 1.01173613921489
## 6: RMD_Year > 0.674490759476595
## 7: RMD_R10_Denominator > -1.93273567078976
## -----------------------------------------------------------------
## Tree 1 Rule 210 Node 66 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("addm", "nsch")
## 5: RMD_Year > 1.01173613921489
## 6: State_Region IN ("D1 New England", "D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## -----------------------------------------------------------------
## Tree 1 Rule 211 Node 67 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 4: Source IN ("addm", "nsch")
## 5: RMD_Year > 1.01173613921489
## 6: State_Region IN ("D5 South Atlantic")
## -----------------------------------------------------------------
## Tree 1 Rule 212 Node 98 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year <= 0.75880210441117
## -----------------------------------------------------------------
## Tree 1 Rule 213 Node 204 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("addm", "medi", "sped")
## 9: RMD_Year <= 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 214 Node 272 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("addm", "medi", "sped")
## 9: RMD_Year > 0.927424794280318
## 10: RMD_R10_Denominator <= -0.931762617041039
## -----------------------------------------------------------------
## Tree 1 Rule 215 Node 273 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("addm", "medi", "sped")
## 9: RMD_Year > 0.927424794280318
## 10: RMD_R10_Denominator > -0.931762617041039
## -----------------------------------------------------------------
## Tree 1 Rule 216 Node 149 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("addm", "nsch", "sped")
## 7: RMD_Year > 0.75880210441117
## 8: Source IN ("nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 217 Node 69 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator <= -0.534315985914185
## 6: Source IN ("medi")
## -----------------------------------------------------------------
## Tree 1 Rule 218 Node 206 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator <= 0.62193991789932
## 7: RMD_R10_Denominator <= 0.444272042570772
## 8: RMD_Year <= 0.927424794280318
## 9: RMD_Year <= 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 219 Node 207 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator <= 0.62193991789932
## 7: RMD_R10_Denominator <= 0.444272042570772
## 8: RMD_Year <= 0.927424794280318
## 9: RMD_Year > 0.590179414542021
## -----------------------------------------------------------------
## Tree 1 Rule 220 Node 151 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator <= 0.62193991789932
## 7: RMD_R10_Denominator <= 0.444272042570772
## 8: RMD_Year > 0.927424794280318
## -----------------------------------------------------------------
## Tree 1 Rule 221 Node 101 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator <= 0.62193991789932
## 7: RMD_R10_Denominator > 0.444272042570772
## -----------------------------------------------------------------
## Tree 1 Rule 222 Node 208 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator > 0.62193991789932
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 1.18035882908404
## 9: RMD_R10_Denominator <= 0.943904700898655
## -----------------------------------------------------------------
## Tree 1 Rule 223 Node 274 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator > 0.62193991789932
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 1.18035882908404
## 9: RMD_R10_Denominator > 0.943904700898655
## 10: Source IN ("addm", "medi", "nsch")
## -----------------------------------------------------------------
## Tree 1 Rule 224 Node 275 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator > 0.62193991789932
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year <= 1.18035882908404
## 9: RMD_R10_Denominator > 0.943904700898655
## 10: Source IN ("sped")
## -----------------------------------------------------------------
## Tree 1 Rule 225 Node 153 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator > 0.62193991789932
## 7: State_Region IN ("D2 Middle Atlantic", "D3 East North Central", "D4 West North Central", "D5 South Atlantic", "D6 East South Central", "D7 West South Central", "D8 Mountain", "D9 Pacific")
## 8: RMD_Year > 1.18035882908404
## -----------------------------------------------------------------
## Tree 1 Rule 226 Node 103 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("medi", "nsch", "sped")
## 5: RMD_R10_Denominator > -0.534315985914185
## 6: RMD_R10_Denominator > 0.62193991789932
## 7: State_Region IN ("D1 New England")
## -----------------------------------------------------------------
## Tree 1 Rule 227 Node 27 Regression (to do - extract predicted value)
##  
## 1: RMD_R10_Denominator > -3.89236192492941
## 2: RMD_Year > 0.421556724672872
## 3: State_Region IN ("D1 New England", "D2 Middle Atlantic")
## 4: Source IN ("addm")
## -----------------------------------------------------------------
## Number of rules in Tree 1: 227
<h3>
Regression Model: Linear Regression (LR)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:48:44 x86_64-pc-linux-gnu 

# Regression model 

# Build a Regression model.

crs$glm <- lm(Prevalence ~ ., data=crs$dataset[crs$train,c(crs$input, crs$target)])

# Generate a textual view of the Linear model.

print(summary(crs$glm))
## 
## Call:
## lm(formula = Prevalence ~ ., data = crs$dataset[crs$train, c(crs$input, 
##     crs$target)])
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11.4991  -1.6532  -0.1294   1.0765  15.7987 
## 
## Coefficients:
##                                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                        12.8301     0.6337  20.247  < 2e-16 ***
## Sourcemedi                         -4.0030     0.5122  -7.816 1.21e-14 ***
## Sourcensch                          5.3449     0.6595   8.105 1.32e-15 ***
## Sourcesped                         -4.8738     0.5521  -8.827  < 2e-16 ***
## State_RegionD2 Middle Atlantic     -1.4687     0.4947  -2.969  0.00305 ** 
## State_RegionD3 East North Central  -1.7105     0.4408  -3.881  0.00011 ***
## State_RegionD4 West North Central  -2.2716     0.3790  -5.994 2.72e-09 ***
## State_RegionD5 South Atlantic      -2.7806     0.3663  -7.592 6.44e-14 ***
## State_RegionD6 East South Central  -3.3525     0.4513  -7.428 2.12e-13 ***
## State_RegionD7 West South Central  -3.9303     0.4557  -8.624  < 2e-16 ***
## State_RegionD8 Mountain            -3.1838     0.3652  -8.719  < 2e-16 ***
## State_RegionD9 Pacific             -2.6588     0.4198  -6.334 3.41e-10 ***
## RMD_Year                            3.8196     0.1258  30.372  < 2e-16 ***
## RMD_R10_Denominator                -0.3919     0.1502  -2.609  0.00919 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.193 on 1170 degrees of freedom
## Multiple R-squared:  0.6907, Adjusted R-squared:  0.6873 
## F-statistic:   201 on 13 and 1170 DF,  p-value: < 2.2e-16
cat('==== ANOVA ====

')
## ==== ANOVA ====
print(anova(crs$glm))
## Analysis of Variance Table
## 
## Response: Prevalence
##                       Df  Sum Sq Mean Sq  F value    Pr(>F)    
## Source                 3 15688.8  5229.6 512.7980 < 2.2e-16 ***
## State_Region           8  1522.1   190.3  18.6566 < 2.2e-16 ***
## RMD_Year               1  9364.8  9364.8 918.2811 < 2.2e-16 ***
## RMD_R10_Denominator    1    69.4    69.4   6.8091  0.009185 ** 
## Residuals           1170 11931.8    10.2                       
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
print("
")
## [1] "\n"
# Time taken: 0.28 secs

# Plot the model evaluation.

ttl <- genPlotTitleCmd("Linear Model",crs$dataname,vector=TRUE)
plot(crs$glm, main=ttl[1])

<h3>
Regression Model: Neural Network (NN)
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:51:47 x86_64-pc-linux-gnu 

# Neural Network 

# Build a neural network model using the nnet package.

library(nnet, quietly=TRUE)

# Build the NNet model.

set.seed(199)
crs$nnet <- nnet(Prevalence ~ .,
    data=crs$dataset[crs$train,c(crs$input, crs$target)],
    size=10, linout=TRUE, skip=TRUE, MaxNWts=10000, trace=FALSE, maxit=100)

# Print the results of the modelling.

cat(sprintf("A %s network with %d weights.\n",
    paste(crs$nnet$n, collapse="-"),
    length(crs$nnet$wts)))
## A 13-10-1 network with 164 weights.
cat(sprintf("Inputs: %s.\n",
    paste(crs$nnet$coefnames, collapse=", ")))
## Inputs: Sourcemedi, Sourcensch, Sourcesped, State_RegionD2 Middle Atlantic, State_RegionD3 East North Central, State_RegionD4 West North Central, State_RegionD5 South Atlantic, State_RegionD6 East South Central, State_RegionD7 West South Central, State_RegionD8 Mountain, State_RegionD9 Pacific, RMD_Year, RMD_R10_Denominator.
cat(sprintf("Output: %s.\n",
    names(attr(crs$nnet$terms, "dataClasses"))[1]))
## Output: Prevalence.
cat(sprintf("Sum of Squares Residuals: %.4f.\n",
    sum(residuals(crs$nnet) ^ 2)))
## Sum of Squares Residuals: 5961.7621.
cat("\n")
print(summary(crs$nnet))
## a 13-10-1 network with 164 weights
## options were - skip-layer connections  linear output units 
##   b->h1  i1->h1  i2->h1  i3->h1  i4->h1  i5->h1  i6->h1  i7->h1  i8->h1  i9->h1 
##   16.82  -14.75    2.09  -15.74  -13.74   -8.97   -8.67   -9.77   -8.20   -8.01 
## i10->h1 i11->h1 i12->h1 i13->h1 
##   -4.46   -8.71   -5.51    0.88 
##   b->h2  i1->h2  i2->h2  i3->h2  i4->h2  i5->h2  i6->h2  i7->h2  i8->h2  i9->h2 
##    2.58   14.66   -6.57   -8.87    2.96    7.46   -0.08    0.15  -15.26  -11.00 
## i10->h2 i11->h2 i12->h2 i13->h2 
##   -1.90    8.82    4.41    0.12 
##   b->h3  i1->h3  i2->h3  i3->h3  i4->h3  i5->h3  i6->h3  i7->h3  i8->h3  i9->h3 
##    5.00    4.70    1.96   -3.69    5.75   -6.40    9.83    2.38   -1.16    2.09 
## i10->h3 i11->h3 i12->h3 i13->h3 
##    0.23   -6.43   -0.45    2.81 
##   b->h4  i1->h4  i2->h4  i3->h4  i4->h4  i5->h4  i6->h4  i7->h4  i8->h4  i9->h4 
##   -3.86    9.61   -8.30   10.31    1.06    4.19   13.48   17.18   11.33    4.70 
## i10->h4 i11->h4 i12->h4 i13->h4 
##    4.25    4.66    3.02   -2.07 
##   b->h5  i1->h5  i2->h5  i3->h5  i4->h5  i5->h5  i6->h5  i7->h5  i8->h5  i9->h5 
##   -6.65   -0.20  -20.42   -5.22    4.58    2.07   12.42    6.07    6.17    1.20 
## i10->h5 i11->h5 i12->h5 i13->h5 
##    3.05    1.19   -0.36    1.49 
##   b->h6  i1->h6  i2->h6  i3->h6  i4->h6  i5->h6  i6->h6  i7->h6  i8->h6  i9->h6 
##   -4.42    5.14   -2.59   -8.49   -2.29    0.88   -6.46  -10.76    6.38   -5.74 
## i10->h6 i11->h6 i12->h6 i13->h6 
##   -1.17    2.19    0.77  -11.94 
##   b->h7  i1->h7  i2->h7  i3->h7  i4->h7  i5->h7  i6->h7  i7->h7  i8->h7  i9->h7 
##   -9.35    0.06   -1.40   -4.66   -4.81    9.20   13.58    3.57   12.79    3.64 
## i10->h7 i11->h7 i12->h7 i13->h7 
##    1.90    7.23   -0.51  -13.88 
##   b->h8  i1->h8  i2->h8  i3->h8  i4->h8  i5->h8  i6->h8  i7->h8  i8->h8  i9->h8 
##   17.29   32.63   -5.50   -8.16   -0.65   -5.89   -6.14   -4.60    4.20   -2.16 
## i10->h8 i11->h8 i12->h8 i13->h8 
##    2.22  -11.96    0.96  -12.98 
##   b->h9  i1->h9  i2->h9  i3->h9  i4->h9  i5->h9  i6->h9  i7->h9  i8->h9  i9->h9 
##  -13.63   -7.98   11.65  -10.50    3.20   10.33  -10.06    0.18    5.01    7.01 
## i10->h9 i11->h9 i12->h9 i13->h9 
##   11.92    6.69  -17.76    2.47 
##   b->h10  i1->h10  i2->h10  i3->h10  i4->h10  i5->h10  i6->h10  i7->h10 
##     2.11     6.72    -0.85    -6.49     0.15   -14.11    -9.57     4.86 
##  i8->h10  i9->h10 i10->h10 i11->h10 i12->h10 i13->h10 
##   -12.31    -2.82   -18.27    -6.34     0.07    16.21 
##   b->o  h1->o  h2->o  h3->o  h4->o  h5->o  h6->o  h7->o  h8->o  h9->o h10->o 
##  11.57  -4.96   3.21   7.50  14.05   7.33  -8.23   4.37  -8.65   3.24  -3.24 
##  i1->o  i2->o  i3->o  i4->o  i5->o  i6->o  i7->o  i8->o  i9->o i10->o i11->o 
## -10.18   7.11 -11.13  -9.55  -7.88 -17.58 -11.38  -6.92  -9.35  -7.31  -7.59 
## i12->o i13->o 
##   3.49  -2.23
cat('\n')
# Time taken: 0.30 secs

Rattle: Evaluate Model (Regression)

Regression: Prevalence

crs$rpart
crs$rf
crs$glm
crs$nnet
<h3>
Rattle: Evaluate Model (Regression): Predicted Versus Observed
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:54:46 x86_64-pc-linux-gnu 

# Evaluate model performance on the testing dataset. 

# RPART: Generate a Predicted v Observed plot for rpart model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$rpart, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Obtain the observed output for the dataset.

obs <- subset(crs$dataset[crs$test, c(crs$input, crs$target)], select=crs$target)

# Handle in case categoric target treated as numeric.

obs.rownames <- rownames(obs)
obs <- as.numeric(obs[[1]])
obs <- data.frame(Prevalence=obs)
rownames(obs) <- obs.rownames

# Combine the observed values with the predicted.

fitpoints <- na.omit(cbind(obs, Predicted=crs$pr))

# Obtain the pseudo R2 - a correlation.

fitcorr <- format(cor(fitpoints[,1], fitpoints[,2])^2, digits=4)

# Plot settings for the true points and best fit.

op <- par(c(lty="solid", col="blue"))

# Display the observed (X) versus predicted (Y) points.

plot(fitpoints[[1]], fitpoints[[2]], asp=1, xlab="Prevalence", ylab="Predicted")

# Generate a simple linear fit between predicted and observed.

prline <- lm(fitpoints[,2] ~ fitpoints[,1])

# Add the linear fit to the plot.

abline(prline)

# Add a diagonal representing perfect correlation.

par(c(lty="dashed", col="black"))
abline(0, 1)

# Include a pseudo R-square on the plot

legend("bottomright",  sprintf(" Pseudo R-square=%s ", fitcorr),  bty="n")

# Add a title and grid to the plot.

title(main="Predicted vs. Observed
 Decision Tree Model
 ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

# RF: Generate a Predicted v Observed plot for rf model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$rf, newdata=na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]))

# Obtain the observed output for the dataset.

obs <- subset(na.omit(crs$dataset[crs$test, c(crs$input, crs$target)]), select=crs$target)

# Handle in case categoric target treated as numeric.

obs.rownames <- rownames(obs)
obs <- as.numeric(obs[[1]])
obs <- data.frame(Prevalence=obs)
rownames(obs) <- obs.rownames

# Combine the observed values with the predicted.

fitpoints <- na.omit(cbind(obs, Predicted=crs$pr))

# Obtain the pseudo R2 - a correlation.

fitcorr <- format(cor(fitpoints[,1], fitpoints[,2])^2, digits=4)

# Plot settings for the true points and best fit.

op <- par(c(lty="solid", col="blue"))

# Display the observed (X) versus predicted (Y) points.

plot(fitpoints[[1]], fitpoints[[2]], asp=1, xlab="Prevalence", ylab="Predicted")

# Generate a simple linear fit between predicted and observed.

prline <- lm(fitpoints[,2] ~ fitpoints[,1])

# Add the linear fit to the plot.

abline(prline)

# Add a diagonal representing perfect correlation.

par(c(lty="dashed", col="black"))
abline(0, 1)

# Include a pseudo R-square on the plot

legend("bottomright",  sprintf(" Pseudo R-square=%s ", fitcorr),  bty="n")

# Add a title and grid to the plot.

title(main="Predicted vs. Observed
 Random Forest Model
 ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

# GLM: Generate a Predicted v Observed plot for glm model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$glm, 
   type    = "response",
   newdata = crs$dataset[crs$test, c(crs$input, crs$target)])

# Obtain the observed output for the dataset.

obs <- subset(crs$dataset[crs$test, c(crs$input, crs$target)], select=crs$target)

# Handle in case categoric target treated as numeric.

obs.rownames <- rownames(obs)
obs <- as.numeric(obs[[1]])
obs <- data.frame(Prevalence=obs)
rownames(obs) <- obs.rownames

# Combine the observed values with the predicted.

fitpoints <- na.omit(cbind(obs, Predicted=crs$pr))

# Obtain the pseudo R2 - a correlation.

fitcorr <- format(cor(fitpoints[,1], fitpoints[,2])^2, digits=4)

# Plot settings for the true points and best fit.

op <- par(c(lty="solid", col="blue"))

# Display the observed (X) versus predicted (Y) points.

plot(fitpoints[[1]], fitpoints[[2]], asp=1, xlab="Prevalence", ylab="Predicted")

# Generate a simple linear fit between predicted and observed.

prline <- lm(fitpoints[,2] ~ fitpoints[,1])

# Add the linear fit to the plot.

abline(prline)

# Add a diagonal representing perfect correlation.

par(c(lty="dashed", col="black"))
abline(0, 1)

# Include a pseudo R-square on the plot

legend("bottomright",  sprintf(" Pseudo R-square=%s ", fitcorr),  bty="n")

# Add a title and grid to the plot.

title(main="Predicted vs. Observed
 Linear Model
 ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

# NNET: Generate a Predicted v Observed plot for nnet model on ADV_ASD_State_R.csv [test].

crs$pr <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input, crs$target)])

# Obtain the observed output for the dataset.

obs <- subset(crs$dataset[crs$test, c(crs$input, crs$target)], select=crs$target)

# Handle in case categoric target treated as numeric.

obs.rownames <- rownames(obs)
obs <- as.numeric(obs[[1]])
obs <- data.frame(Prevalence=obs)
rownames(obs) <- obs.rownames

# Combine the observed values with the predicted.

fitpoints <- na.omit(cbind(obs, Predicted=crs$pr))

# Obtain the pseudo R2 - a correlation.

fitcorr <- format(cor(fitpoints[,1], fitpoints[,2])^2, digits=4)

# Plot settings for the true points and best fit.

op <- par(c(lty="solid", col="blue"))

# Display the observed (X) versus predicted (Y) points.

plot(fitpoints[[1]], fitpoints[[2]], asp=1, xlab="Prevalence", ylab="Predicted")

# Generate a simple linear fit between predicted and observed.

prline <- lm(fitpoints[,2] ~ fitpoints[,1])

# Add the linear fit to the plot.

abline(prline)

# Add a diagonal representing perfect correlation.

par(c(lty="dashed", col="black"))
abline(0, 1)

# Include a pseudo R-square on the plot

legend("bottomright",  sprintf(" Pseudo R-square=%s ", fitcorr),  bty="n")

# Add a title and grid to the plot.

title(main="Predicted vs. Observed
 Neural Net Model
 ADV_ASD_State_R.csv [test]",
    sub=paste("Rattle", format(Sys.time(), "%Y-%b-%d %H:%M:%S"), Sys.info()["user"]))
grid()

<h3>
Rattle: Evaluate Model (Regression): Score/Write predicted results to CSV file.
</h3>

#=======================================================================
# Rattle timestamp: 2019-12-30 11:59:50 x86_64-pc-linux-gnu 

# Score the testing dataset. 

# Obtain predictions for the Decision Tree model on ADV_ASD_State_R.csv [test].

crs$pr_rpart <- predict(crs$rpart, newdata=crs$dataset[crs$test, c(crs$input)])

# Obtain predictions for the Random Forest model on ADV_ASD_State_R.csv [test].

crs$pr_rf <- predict(crs$rf, newdata=na.omit(crs$dataset[crs$test, c(crs$input)]))

# Obtain predictions for the Linear model on ADV_ASD_State_R.csv [test].

crs$pr_glm <- predict(crs$glm, 
   type    = "response",
   newdata = crs$dataset[crs$test, c(crs$input)])

# Obtain predictions for the Neural Net model on ADV_ASD_State_R.csv [test].

crs$pr_nnet <- predict(crs$nnet, newdata=crs$dataset[crs$test, c(crs$input)])

# Extract the relevant variables from the dataset.

sdata <- crs$dataset[crs$test,]

# Output the combined data.

write.csv(cbind(sdata, crs$pr_rpart, crs$pr_rf, crs$pr_glm, crs$pr_nnet), file="../reference/R rattle/ADV_ASD_State_R_test_score_all_Prevalence.csv", row.names=FALSE)
<a href="">
     <img src="" width="750" align="center">
</a>

Rattle: Improve Model

Tune hyperparameters

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     <img src="" width="750" align="center">
</a>

Rattle: Save Model & Log

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</a>

Workshop Submission

<h3>
    What to submit?
</h3>
<p>
    Create predictive model for Multi Class Classification of ASD Prevalence Risk Level (Low, Medium, High, Very High) using xgboost package's Extreme Gradient Boosting algorithm.
</p>

References:

XGBoost support added to Rattle: A demo using Kaggle Competition Credit Card Fraud Detection: https://blog.revolutionanalytics.com/2017/07/xgboost-support-added-to-rattle.html

https://github.com/dd-consulting/DDC-Data-Science-R/blob/master/HousePriceAnalysisPrediction/codeR/House%20prices_%20Lasso%2C%20XGBoost%2C%20and%20a%20detailed%20EDA.pdf

https://github.com/dd-consulting/DDC-Data-Science-R/blob/master/Google%20Analytics%20Customer%20Revenue%20Prediction/code/Google%20Analytics%20Customer%20Revenue%20Prediction%20EDA.pdf

# Write your code below and press Shift+Enter to execute 

Double-click here for the solution.

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     <img src="" width="750" align="center">
</a>

Excellent! You have completed the workshop notebook!

Connect with the author:

This notebook was written by GU Zhan (Sam).

Sam is currently a lecturer in Institute of Systems Science in National University of Singapore. He devotes himself into pedagogy & andragogy, and is very passionate in inspiring next generation of artificial intelligence lovers and leaders.

Copyright © 2020 GU Zhan

This notebook and its source code are released under the terms of the MIT License.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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</a>

Appendices

<h3>
Interactive workshops: < Learning R inside R > using swirl() (in R/RStudio)
</h3>

https://github.com/telescopeuser/S-SB-Workshop

<a href="https://github.com/dd-consulting">
     <img src="../reference/GZ_logo.png" width="60" align="right">
    https://github.com/dd-consulting
</a>